Traffic surge management for points of presence

Information

  • Patent Grant
  • 10469355
  • Patent Number
    10,469,355
  • Date Filed
    Monday, November 13, 2017
    6 years ago
  • Date Issued
    Tuesday, November 5, 2019
    4 years ago
Abstract
A system, method, and computer-readable medium for point of presence (POP) based traffic surge detection and mitigation are provided. The system detects a traffic surge for a target group of resources directed at a source POP based on the target group's rank shifts and volume changes among recent time intervals. The system mitigates the detected traffic surge by identifying destination POPs with spare capacity and routing at least a portion of incoming requests for the target group of resources to the destination POPs in accordance with their spare capacities.
Description
BACKGROUND

Generally described, computing devices and communication networks can be utilized to exchange information. In a common application, a computing device can request content from another computing device via the communication network. For example, a user at a personal computing device can utilize a software browser application to request a Web page or application from a server computing device via the Internet. In such embodiments, the user computing device can be referred to as a client computing device (“client”) and the server computing device can be referred to as a content provider.


Content providers are generally motivated to provide requested content to client computing devices often with consideration of efficiency, reliability, and/or cost associated with the transmission of the content. For larger scale implementations, a content provider may receive content requests from a high volume of client computing devices which can place a strain on the content provider's computing resources. Additionally, the content requested by the client computing devices may have a number of components, which can further place additional strain on the content provider's computing resources.


Some content providers attempt to facilitate the delivery of requested content, such as Web pages or resources identified in Web pages, through the utilization of a content delivery network (“CDN”) service provider. A CDN service provider typically maintains a number of computing devices, generally referred to as “points of presence” or “POPs” in a communication network. The service provider or POPs can include one or more domain name service (“DNS”) computing devices that can process DNS queries from client computing devices. Additionally, the POPs can include network resource storage component that maintain content from various content providers. In turn, content providers can instruct, or otherwise suggest to, client computing devices to request some, or all, of a content provider's content from the CDN service provider's computing devices. As with content providers, CDN service providers are also generally motivated to provide requested content to client computing devices often with consideration of efficiency, reliability, and/or cost associated with the transmission of the content.





BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages will become more readily appreciated as the same become better understood by reference to the following detailed description, when taken in conjunction with the accompanying drawings. Throughout the drawings, reference numbers may be re-used to indicate correspondence between referenced elements. The drawings are provided to illustrate example embodiments described herein and are not intended to limit the scope of the disclosure.



FIG. 1 is a block diagram illustrative of a content delivery environment including a number of client computing devices, a number of content providers, and a content delivery service provider;



FIG. 2 is a block diagram of the content delivery environment of FIG. 1 illustrating the detection of a traffic surge for network resources;



FIG. 3 is a block diagram of the content delivery environment of FIG. 1 illustrating the mitigation of a traffic surge for network resources;



FIG. 4 is a flowchart illustrative of a traffic surge detection routine implemented by a content delivery network service provider; and



FIG. 5 is a flowchart illustrative of a traffic surge mitigation routine implemented by a content delivery network service provider.



FIG. 6 is a flowchart illustrative of a routine implemented by a content delivery network service provider to conclude traffic surge mitigation.



FIG. 7 is an illustrative functional block diagram of a computing device for detecting and mitigating traffic surge.





DETAILED DESCRIPTION

Generally described, the present disclosure is directed to the management and routing of requests from client computing device for network resources. Specifically, aspects of the disclosure will be described with regard to detection of a traffic surge for network resources at points of presence (POPs), based on analyses of current and previous content request volume data. Additionally, aspects of the disclosure will be described with regard to mitigation of a traffic surge via content request routing to multiple POPs, based on traffic surge data and POP capacity information. Illustratively, a traffic surge may correspond to an unexpected and massive surge in volume of requests received at a POP for a target group of network resources. For example, one type of traffic surge may correspond to flash crowd traffic, such as where a Web site suddenly catches the attention of a large number of users. Illustratively, this may occur concurrently with reports of breaking news, releases of revolutionary products, openings of popular events, etc., when relevant Web sites may see abrupt surge in traffic. A traffic surge may include legitimate user requests as well as malicious attacks, and may cause slow down or temporary unavailability of content serving functionalities or devices, and therefore should be detected and mitigated. In particular, a traffic surge should not adversely affect the experience of users who do not contribute to the traffic surge (e.g., users who are not requesting any resource of the target group).


In accordance with an illustrative embodiment, a content delivery network (CDN) service provider receives content requests for network resources associated with various content providers. Each content provider may set up groups of network resources (e.g., corresponding to Web pages, Web applications, Web sites, or portions thereof) that the CDN service provider may assist in content delivery. The CDN service provider may include a request routing service for routing incoming content requests to appropriate POPs for processing. For example, in response to a DNS query corresponding to a requested resource, a CDN service provider may select a POP to serve the resource request based on a geographic proximity between the POP and the requesting client device.


At regular time intervals (e.g., every minute), a traffic surge detection service of the CDN service provider obtains data regarding request volumes for various groups of resources received at each POP during a most recent period of time (e.g., the minute that just passed). The data may be a list of resource groups ordered by their associated request volume during the most recent period of time. Based on the request volume data corresponding to temporally ordered time periods, the traffic surge detection service may determine resource groups that begin to receive a traffic surge at any POP in substantially real time. In addition, the traffic surge detection service may obtain data indicating the magnitude, or rate, of change in volume of requests for a resource group. For example, this data may indicate that a certain resource group experienced a spike in requests in a 10 second span that exceeds a certain threshold (e.g, a percentage) of the normal request fluctuations. This could also indicate that, while it may not be problematic for requests to spike from 10 requests to 50 requests in a matter of five minutes, that same increase in requests over five seconds may be indicative of a traffic surge.


For example, for each POP, the traffic surge detection service may identify a resource group that is ranked within the top 10 groups by request volume for the most recent time period. The ranking may also take into account and be based upon the rate of change of resource groups. The traffic surge detection service may then determine whether the identified group also appears within the top 10 groups by request volume during a specified number of time periods prior to the most recent time period. If the identified resource group is not one of the top 10 requested groups for any prior time periods, the traffic surge detection service may label the identified resource group as a candidate group for further determination.


For the candidate group, the traffic surge detection service determines a shift in its rank by request volume as between prior time periods and the most recent time period. The traffic surge detection service may further determine a magnitude of change in request volume for the candidate group between prior time periods and the most recent time period, or the rate of change in request volume over a particular time period or a particular set of time periods. Applying predetermined or dynamically generated thresholds to the change of rank and/or magnitude in terms of request volume, the traffic surge detection service may determine that the candidate group is currently receiving a traffic surge. The traffic surge detection service may then generate a traffic surge alert including information about the affected POP, the identified group of resources, the most recent request volume corresponding to the group, etc.


The traffic surge alert may be provided to a traffic surge mitigation service of the CDN service provider so that the traffic surge can be mitigated. The traffic surge mitigation service may constantly estimate current spare capacities of individual POPs for processing content requests. Illustratively, at regular time intervals (e.g., every minute), each POP may provide data regarding a total volume of requests that are processed by the POP during the most recent period of time. The estimated spare capacity may correspond to a difference between a maximum quantity of content requests that can be processed by the POP (e.g., as limited by its networking or computational capacity) and the total volume of requests processed during the most recent period of time.


Upon receipt of a traffic surge alert for a source POP that identifies a target resource group as receiving a traffic surge, the traffic surge mitigation service determines whether the source POP may absorb the surged traffic based on its estimated spare capacity. If not, the traffic surge mitigation service attempts to identify one or more destination POPs to spread the surged traffic. The traffic surge mitigation service may identify a list of destination POPs based on a combination of factors, such as their corresponding estimated spare capacity, geographic or network-based proximity to the source POP or clients generating the traffic surge, groups of resources currently being served, latency, bandwidth, other POP performance factors, combination of the same, or the like.


The traffic surge mitigation service may distribute the traffic surge request volume, as reported in the traffic surge alert, across the source POP and a sufficient number of identified destination POPs based on their corresponding estimated spare capacities. The traffic surge mitigation service may then calculate a corresponding routing weight for each of the source and destination POPs that will serve future traffic, based on their respective proportions of the traffic surge request volume as distributed. The traffic surge mitigation service may then cause modification of a routing policy or mechanism, which can be implemented by the routing service of the CDN service provider, for routing incoming requests for network resources corresponding to the target group, in accordance with the calculated routing weights. For example, the modified routing policy may enable the routing service to probabilistically route any incoming requests for the target group received during the next period of time to the source POP or one of the destination POPs based on their respective routing weights.


The traffic surge mitigation service continues to monitor the request volumes for the target group received at the source and destination POPs as incoming traffic is routed during subsequent time periods. In doing so, the traffic surge mitigation service may calculate an aggregate request volume for the target group based on respective volumes received at each applicable POP. For each of the subsequent time periods, the traffic surge mitigation service may adjust the routing weights, adding or removing destination POPs, or otherwise modifying the routing policy or mechanism in response to changes in the aggregate request volume for the target group. If the aggregate request volume returns to a level manageable by the source POP alone (e.g., within a threshold of an average request volume for a number of time periods prior to the detection of traffic surge), the traffic surge mitigation service may terminate the mitigation process and cause the routing service to resume its usual routing functionalities with respect to incoming traffic for the target group.


Although various aspects of the disclosure will be described with regard to illustrative examples and embodiments, one skilled in the art will appreciate that the disclosed embodiments and examples should not be construed as limiting. For example, although aspects of the disclosure will be described with regard to specific service providers such as a CDN service provider, one skilled in the relevant art will appreciate that aspects of the disclosure may be implemented by various types of service providers or that a service provider implementing aspects of the disclosure is not required to have the specific components utilized in the illustrative examples.



FIG. 1 is a block diagram illustrative of content delivery environment 100 for the management and processing of content requests. As illustrated in FIG. 1, the content delivery environment 100 includes a number of client computing devices 102 (“clients”) for requesting content from a content provider and/or a CDN service provider. In an illustrative embodiment, the clients 102 can correspond to a wide variety of computing devices including personal computing devices, laptop computing devices, hand-held computing devices, terminal computing devices, mobile devices, wireless devices, various electronic devices and appliances and the like.


In an illustrative embodiment, the clients 102 include necessary hardware and software components for establishing communications over a communication network 108. For example, the client computing devices 102 may be equipped with networking equipment and browser software applications that facilitate communications via the communication network 108. The network 108 can be a publicly accessible network of linked networks, possibly operated by various distinct parties, such as the Internet. In other embodiments, the network 108 may include a private network, personal area network (“PAN”), LAN, WAN, cable network, satellite network, any other medium of computer data transfer, or some combination thereof.


The clients 102 may also include necessary hardware and software components for requesting content from network entities in the form of an originally requested resource that may include identifiers to two or more embedded resources that need to be requested. Further, the clients 102 may include or be associated with necessary hardware and software components, such as browser software applications, plugins, scripts, etc., for fulfilling the original resource request and each embedded resource request. In other embodiments, the client computing devices 102 may be otherwise associated with an external proxy application or device, as well as any other additional software applications or software services, used in conjunction with requests for content.


Although not illustrated in FIG. 1, each client 102 may utilize some type of DNS resolver component, that generates DNS queries attributed to the client computing device. In one embodiment, the DNS resolver component may be provided by an enterprise network to which the client 102 belongs. In another embodiment, the DNS resolver component may be provided by an Internet Service Provider (ISP) that provides the communication network connection to the client 102.


The content delivery environment 100 also includes one or more content providers 104 in communication with the clients 102 via the communication network 108. The content provider 104 illustrated in FIG. 1 corresponds to a logical association of one or more computing devices associated with a content provider. Specifically, the content provider 104 can include one or more server computing devices for obtaining and processing requests for content (such as Web pages) from the clients 102. The content provider 104 can further include one or more computing devices for obtaining and processing requests for network resources from the CDN service provider. One skilled in the relevant art will appreciate that the content provider 104 can be associated with various additional computing resources, such additional computing devices for administration of content and resources, DNS name servers, and the like.


With continued reference to FIG. 1, the content delivery environment 100 further includes a CDN service provider 106 in communication with the clients 102 and the content providers 104 via the communication network 108. The CDN service provider 106 illustrated in FIG. 1 corresponds to a logical association of one or more computing devices associated with a CDN service provider. Specifically, the CDN service provider 106 can include a number of points of presence (“POP”) locations 116 that correspond to nodes on the communication network 108. Each POP 116 may include a number of DNS server computing devices for resolving DNS queries from the clients 102. Each POP 116 may also include a number of cache server computing devices for storing resources from content providers and transmitting various requested resources to various client computers. Further, although the POPs 116 are illustrated in FIG. 1 as logically associated with the CDN service provider 106, the POPs can be geographically distributed throughout the communication network 108 to serve the various demographics of clients 102. Additionally, one skilled in the relevant art will appreciate that the CDN service provider 106 can be associated with various additional computing resources, such additional computing devices for administration of content and resources, and the like.


The CDN service provider 106 can include a request routing service 120 for routing content requests to various POPs 116 for processing, a traffic surge detection service 130 for detecting traffic surges for each POP 116, and a traffic surge mitigation service 140 for determining traffic surge mitigation strategies. For example, the request routing service 120 may include or otherwise be associated with a number of DNS server computing devices for resolving DNS queries from the clients 102. The DNS server computing devices associated with the request routing service 120 may or may not include DNS devices associated with individual POPs 116. Illustratively, the request routing service 102 may implement various routing policies or mechanisms to facilitate the traffic surge detection and mitigation functionalities disclosed herein.


The traffic surge detection service 130 can implement various computational, statistical, or machine learning methods to detect traffic surges based on volumes of content requests received at individual POPs 116 for various groups of network resources. Illustratively, the traffic surge detection service 130 may obtain request volume data corresponding to consecutive time intervals from the POPs 116. The traffic surge detection service 130 may identify resource groups corresponding to high request volumes and compare their rankings in terms of request volume across a number of recent and/or historical time intervals. The traffic surge detection service 130 may also compare changes in the magnitude of request volumes across time intervals for the highly requested resource groups. The traffic surge detection service 130 may conduct these comparisons with predetermined or dynamically generated thresholds or criteria, and determine resource groups that are considered targets of a traffic surge for each POP 116.


In some embodiments, the traffic surge detection service 130 may detect traffic surges based on rate of change in traffic volume. Illustratively, the traffic surge detection service 130 may estimate first and/or second derivatives of request volume as a function of time, based on the traffic volumes as sampled from each time period. The traffic surge detection service 130 may determine whether the estimated first and/or second derivatives exceeds predetermined thresholds for a recent time. As another example, the traffic surge detection service 130 may compute a correlation coefficient between request volume and time (or time periods) over request volumes reported in a number of recent time periods, and determine whether the coefficient exceeds certain threshold. These methods can be used independently or in conjunction with other analysis and comparisons as described above.


The traffic surge mitigation service 140 can implement various computational methods for developing traffic surge mitigation strategies. Illustratively, the traffic surge mitigation service 140 may estimate current or future spare capacities of various POPs 116 for processing content requests, determine whether a source POP has capacity to absorb detected traffic surge, or identify destination POPs that may be suitable for handling at least a portion of the surged traffic. Additionally, the traffic surge mitigation service 140 may create or update request routing policies implemented by the request routing service 120, for routing future requests for any target resource groups receiving a traffic surge in accordance with determined mitigation strategies.


Further, these modules or components may include additional components, systems, and subsystems for facilitating the methods and processes. In various embodiments, reference to the request routing service 120, the traffic surge detection service 130, or the traffic surge mitigation service 140 may include multiple computing devices working in conjunction to facilitate the functionalities disclosed herein. For example, in various embodiments, the services may be distributed through a network or implemented by one or more virtual machine instances. Additionally or alternatively, the request routing service 120, the traffic surge detection service 130, or the traffic surge mitigation service 140 may be centralized in one computing device, and/or be distributed across several computing devices.


With reference now to FIG. 2 and FIG. 3, the interaction between various components of the content delivery environment 100 of FIG. 1 will be illustrated. For purposes of the example, however, the illustration has been simplified such that many of the components utilized to facilitate communications are not shown. One skilled in the relevant art will appreciate that such components can be utilized and that additional interactions would accordingly occur without departing from the spirit and scope of the present disclosure.



FIG. 2 is a block diagram of the data communication environment 100 of FIG. 1 illustrating the detection of a traffic surge for network resources. As illustrated in FIG. 2, at (1), one or more clients 102 transmit content requests to the CDN service provider 106 for network resources associated with various content providers. As described above, the network resources may correspond to different groups in accordance with their corresponding criteria. For example, each content provider may define one or more groups of network resources (e.g., as corresponding to Web pages, Web applications, Web sites, or portions thereof) that the CDN service provider may assist in delivering to clients 102.


In accordance with an illustrative embodiment, a content request may include a DNS query for a resource's uniform resource locator (URL). After resolution of the DNS query, a content retrieval request may follow accordingly, based on common network protocols, such as the hypertext transfer protocol (“HTTP”). The URLs for requested network resources may indicate or otherwise provide information for the CDN service provider 106 to correlate each content request to a specific group of network resources. For example, the URL may include a designation of domain or subdomain, which corresponds to an identification of one of the network resource groups defined by various content providers 104. In some embodiments, the content requests may not be directly transmitted from clients 102 to the CDN service provider 106. For example, there may be one or more intermediate entities, such as DNS resolvers or proxy devices, between the clients 102 and the CDN service provider 106.


At (2), the CDN service provider 106 processes the content requests. In some embodiments, the content requests are received at the request routing service 120. The request routing service 120 may route each request to an appropriate POP 116 in accordance with existing routing policies. For example, the request routing service 120 may resolve DNS queries by replying to the queries with network routing information, such as Internet Protocol (IP) addresses, for the selected POPs 116. The selection of a POP to serve the request can be based on a network-based proximity between the POP and the requesting client 102 or an intermediate entity. Following the routing, individual POPs 116 may receive content requests directed thereto. In other embodiments, the request routing service 120 is implemented in a distributed fashion at individual POPs 116. In these embodiments, certain content requests received at one POP may or may not be routed to another POP.


At (3), each POP 116 generates data regarding request volume (e.g., a total number of requests during a certain period of time) received at the POP for various groups of network resources, and transmits the request volume data to the traffic surge detection service 130 or to a data repository that the traffic surge detection service 130 has access to. The data can be transmitted at regular time intervals (e.g., every 10 seconds), upon request by the traffic surge detection service 130, or based on the occurrence of triggering events. Illustratively, the data may be a list of resource groups associated with their respective request volume during a most recent period of time (e.g., the 30 seconds that just passed). The time periods for each round of request volume can be consecutive, disjoint, or overlapping. For example, request volumes can be calculated on a 60-second basis while the data generation and transmission can be performed every 30 seconds, that is, there can be an underlying 30-second overlap of time between the request volume data of any two consecutive data transmissions. As described above, rate of changes within a time period of among several time periods can be calculated as well.


The number of resource groups included in the transmitted data may be predetermined. For example, the data may include a set of top 50 groups of resources as measured by their respective request volume. Alternatively or in addition, the number of resource groups included in the data may be dynamically determined. For example, only those groups associated with request volumes, or request volume rates of change, higher than a threshold value will be included. In some embodiments, the data includes any and all resource groups that a respective POP 116 has assisted in content delivery during the most recent period of time.


At (4), the traffic surge detection service 130 detects a traffic surge based on the request volume data for various groups of network resources. In some embodiments, the traffic surge detection service 130 may analyze the request volume data for each POP 116 individually. For example, the traffic surge detection service 130 may parse the request volume data of a POP and identify 10 resource groups (e.g., corresponding to 10 different Web pages) that are associated with the highest 10 request volumes received at the POP for the most recent time period. The traffic surge detection service 130 may then determine whether any of the identified 10 groups was not associated with a sufficiently high request volume in a number of time periods prior to the most recent time period. Illustratively, this can be achieved by comparing the identified 10 resource groups against a specified number (e.g., an integer equal to or greater than 10) of top groups as ranked by request volume during previous time periods. In some embodiments, the ranking of groups can be based on their respective rate of change in request volumes, which can be estimated or calculated based on methods described above or known in relevant technical fields.


If all identified resource groups consistently appear within the top ranks for a number of previous time periods, they are not considered traffic surge targets because there is no abrupt surge of request volume. If an identified resource group is not one of the top requested groups for some previous time periods, the traffic surge detection service 130 may label the identified resource group as a candidate group for further determination. For the candidate group, the traffic surge detection service 130 may determine a shift in its rank by request volume as between one or more previous time periods and the most recent time period. If the shift in rank exceeds a threshold measure, the identified resource group may be considered a target receiving a traffic surge.


Alternatively or in addition, the traffic surge detection service 130 may determine a magnitude of change in request volume for the candidate group between previous time periods and the most recent time period. For example, the traffic surge detection service 130 may calculate a difference or ratio between a request volume of the most recent time period and an average request volume of a specified number of previous time periods. Applying a predetermined or dynamically generated threshold to the calculated difference or ratio, the traffic surge detection service 130 may determine that the candidate group is currently receiving a traffic surge.


The traffic surge detection service 130 may then generate a traffic surge alert including information about the affected POP, the identified group of resources, the most recent request volume corresponding to the group, etc. The generated traffic surge alerts can be transmitted to the traffic surge mitigation service 140, another service, or a system administrator for further processing.



FIG. 3 is a block diagram of the content delivery environment 100 of FIG. 1 illustrating the mitigation of a traffic surge for network resources. As illustrated in FIG. 3, at (1), the traffic surge detection service 130 provides traffic surge data to the traffic surge mitigation service 140. The traffic surge data may include the traffic surge alerts generated by traffic surge detection service 130 as well as any associated metadata, such as information regarding the underlying time periods for determining a traffic surge. In some embodiments, the traffic surge data may be transmitted directly between the services. In other embodiments, the traffic surge data can be maintained by a database or data store accessible to the traffic surge mitigation service 140.


At (2), the traffic surge mitigation service 140 obtains information related to determining spare capacity of individual POPs 116 for processing content requests for various groups of network resources. Illustratively, at regular time intervals (e.g., every 10 seconds), each POP 116 may transmit or otherwise provide data regarding a total volume of requests processed by the POP during the most recent period of time to the traffic surge mitigation service 140. Again, the length of the time interval between two consecutive reports of request volumes may or may not be the same as the time period that serves as basis for calculating the request volumes. Each POP 116 may also provide the traffic surge mitigation service 140 information about content currently being served by the POP 116, current maximum capacity of the POP 116 for serving certain types of content requests, latency, bandwidth, or other performance metrics associated with the POP 116. In some embodiments, another intermediary service or system collects necessary information from individual POPs 116, calculates or estimates spare capacities of the POPs for processing content requests of various groups, and provides the spare capacity information to the traffic surge mitigation service 140 at regular or varied time intervals or upon request.


At (3), for each traffic surge alert that identifies a target resource group as receiving a traffic surge at a source POP 116, the traffic surge mitigation service 140 determines whether the source POP may absorb the traffic surge without adversely affecting its performance. Illustratively, the traffic surge mitigation service 140 may estimate a current spare capacity of a POP 116 for processing requests for the target resource group based on the information obtained at (2). For example, the estimated spare capacity may correspond to a difference between a maximum quantity of content requests that can be processed by the POP 116 (e.g., as limited by its networking or computational capacity) during a future time period and the total volume of requests processed during the most recent period of time. In some embodiments, a cushion capacity (e.g., 10% of the maximum request processing capacity) is reserved for each POP 116 and will be carved out of the estimation. In other words, the maximum capacity may be reduced by the cushion capacity for purposes of estimating the spare capacity.


If the traffic surge mitigation service 140 determines that the source POP 116 does not have sufficient spare capacity to absorb the traffic surge traffic, for example, by comparing its estimated spare capacity against the traffic surge request volume as reported in the traffic surge alert, the traffic surge mitigation service 140 starts identifying one or more destination POPs 116 to spread the surged traffic. The traffic surge mitigation service 140 may identify a list of destination POPs based on a combination of factors, such as their corresponding estimated spare capacity, geographic or network-based proximity to the source POP or clients generating the traffic surge, groups of resources currently being served, latency, bandwidth or POP performance factors, etc. For example, the traffic surge mitigation service 140 may sort a set of POPs 116 based on their geographic distances to the source POP 116 and identify from the set a number of destination POPs 116 that are closest to the source POP 116. The traffic surge mitigation service 140 may also confirm that an aggregate of the estimated spare capacity of the identified destination POPs 116 (when combined with that of the source POP, in some embodiments) are sufficient to handle the traffic surge request volume as reported in the traffic surge alert.


The traffic surge mitigation service 140 may then calculate a corresponding routing weight for each of the source and destination POPs, based on their corresponding estimated spare capacity to process requests for the target group of traffic surge. In some embodiments, the routing weight may further depend on associated latency, bandwidth, estimated timing of peak or non-peak load, or other POP performance factors. The traffic surge mitigation service 140 may then determine a policy or mechanism for routing incoming content requests for network resources corresponding to the target group, in accordance with the calculated routing weights. In some embodiments, the modified routing policy may correspond to a deterministic temporal order of the source POP and the destination POPs that conforms to their routing weights distribution (e.g., always route a first 4 incoming requests to the source POP, the next 2 requests to destination POP 1, . . . , the next 3 requests to destination POP n, and repeat the sequence). In other embodiments, the modified routing policy may correspond to a probabilistic or otherwise randomized decision scheme, where a resource request is more likely to be routed to a POP associated with a larger routing weight.


At (4), the traffic surge mitigation service 140 may communicate the determined routing policy to the routing service 120 or otherwise causing the routing service 120 to update routing policies or mechanisms accordingly. This enables the routing service 120, for a future period of time, to route incoming requests for the target group in accordance with the determined routing policy. Thereafter, the traffic surge mitigation service 140 determines updated routing policies based on new estimates of spare capacities associated with the source and/or destination POPs as described above. This process can be repeated at specified time intervals (e.g., every minute) until no more traffic surge alerts for the target resource group is generated for the source POP. In some embodiments, when a destination POP is selected and starts receiving a portion of surged traffic offloaded from the source POP, traffic surge alerts with respect to the same target group may be generated for the destination POP. In these embodiments, the traffic surge mitigation service 140 may disregard the traffic surge alerts for the target group generated by the destination POPs until the offloading ends.



FIG. 4 is a flowchart illustrative of a traffic surge detection routine implemented by a CDN service provider 106. The routine starts at block 400. At block 402, the CDN service provider 104 obtains current data regarding request volume for network resource groups from each POP 116. Illustratively, the data can be transmitted from each POP 116 to the CDN service provider 106 at regular time intervals (e.g., every minute), upon request by the traffic surge detection service 130, or based on the occurrence of triggering events. The data may be a list of resource groups associated with their respective request volume during a most recent period of time (e.g., the 30 seconds that just passed). As describe above, the time periods for each round of request volume can be consecutive, disjoint, or overlapping.


At block 404, the CDN service provider 106 compares current volume data against prior volume data received from any specific POP 116. For example, the CDN service provider 106 may identify all resource groups that are ranked (e.g., by request volume) higher than a pre-determined first threshold position in the list of resource groups or account for a respective volume higher than can be processed by a certain proportion or percentage of the specific POP's processing capacity, in the most recent time period. The CDN service provider 106 may then determine whether any of the identified groups is ranked below a second threshold position, in some time period(s) prior to the most recent time period. In some embodiments, the second threshold position may be determined based on the identified group's ranking in the most recent time period. For example, the second threshold position may be a function of the identified group's rank in the most recent time period, such as a multiple of the rank value plus a constant offset number.


As described above, in some embodiments, the CDN service provider 106 may detect traffic surges based on rate of change in traffic volume. Illustratively, the CDN service provider 106 may estimate first and/or second derivatives of request volume as a function of time, based on the volumes as sampled from each time period. The CDN service provider 106 may determine whether the estimated first or second derivative exceeds a predetermined threshold for a recent time. As another example, the CDN service provider 106 may compute a correlation coefficient between request volume and time (or time periods) over request volumes reported in a number of recent time periods, and determine whether the coefficient exceeds certain threshold. These methods can be applied independently or in conjunction with other analysis and comparisons as described above.


At block 406, the CDN service provider 106 determines whether a resource group is currently receiving a traffic surge based on the comparison. As described above, if all identified resource groups consistently appear within the top ranks for a number of previous time periods, the resource groups are not considered traffic surge targets because there is no abrupt surge of request volume. If an identified resource group is not one of the top requested groups in some previous time periods (e.g., based on the second threshold positions), the CDN service provider 106 may label the identified resource group as a candidate group for further determination. For the candidate group, the CDN service provider 106 may determine a value change between a function of its ranks (e.g., a weighted average) in multiple previous time periods and its rank in the most recent time period. If the change exceeds a threshold measure, which can be predetermined or dynamically calculated based on any previous or current rank of the candidate group, the candidate group may be considered a target receiving a traffic surge.


Alternatively or in addition, the CDN service provider 106 may determine a magnitude of change in request volume for the candidate group between previous time periods and the most recent time period. For example, the traffic surge detection service 130 may calculate a difference or ratio between a request volume of the most recent time period and a weighted average of request volumes for some previous time periods. Similar to how the rankings may be utilized mathematically, predetermined or dynamically generated thresholds can be applied to the calculated difference or ratio, and the CDN service provider 106 may determine whether the candidate group is receiving a traffic surge. If the CDN service provider 106 determines that the identified resource group is receiving a traffic surge, the routine of FIG. 4 proceeds to block 408. Otherwise, the routine returns to block 402, where more recent data regarding request volume is obtained.


If the routine proceeds to block 408, the CDN service provider 106 provides traffic surge data as determined. The CDN service provider 106 may generate a traffic surge alert including information about the affected POP, the identified group of resources, the most recent request volume corresponding to the group, etc. The traffic surge data can be utilized by the CDN service provider 106, another service, or a system administrator for purposes of mitigating traffic surge. The routine of FIG. 4 ends at block 410.



FIG. 5 is a flowchart illustrative of a traffic surge mitigation routine implemented by a CDN service provider 106. The routine starts at block 500. At block 502, the CDN service provider 106 obtains traffic surge data for a source POP 116. The traffic surge data may include the traffic surge alerts generated by the CDN service provider 106 as well as any associated metadata, such as information regarding the underlying time periods for determining a traffic surge.


At block 504, the CDN service provider 106 determines whether a surged demand for target network resource group as indicated in the traffic surge data exceeds a spare capacity of the source POP 116. Illustratively, the CDN service provider 106 may estimate a current spare capacity of a POP 116 based on a maximum capacity of the POP for processing requests and a total volume of requests currently processed by the POP. For example, the estimated spare capacity may correspond to a difference between a maximum quantity of content requests that can be processed by the POP 116 (e.g., as limited by its networking or computational capacity) during a future time period and a total volume of requests processed at the POP during the most recent period of time. As described above, in some embodiments, a cushion capacity is reserved for each POP 116 and will reduce the maximum capacity for purposes of spare capacity estimation.


If the CDN service provider 106 determines that the source POP 116 has sufficient spare capacity to absorb the traffic surge (e.g., its estimated spare capacity exceeds the traffic surge request volume as reported in the traffic surge alert by a predetermined threshold measure), the routine proceeds to an end at block 510. Otherwise, at block 506, the CDN service provider 106 identifies one or more destination POPs 116 with spare capacity to spread the surged traffic. Illustratively, the CDN service provider 106 may initially identify a destination POP closest to the source POP among all the POPs 116. The determination of distance between the destination POP and source POP can be based on various factors, such as estimated spare capacity, geographic or network-based proximity to the source POP or clients generating the traffic surge, groups of resources currently being served, latency, bandwidth, reliability or performance factors, combinations of the same, or the like. In some embodiments, POPs 116 associated with a current traffic surge alert themselves are excluded from being identified as a destination POP.


In some embodiments, once a destination POP 116 is identified, the CDN service provider 106 calculates an aggregate spare capacity between the source and the identified destination POP(s). If the aggregate spare capacity is still not sufficient to absorb the traffic surge (e.g., the estimated traffic surge traffic exceeds the aggregate spare capacity), the CDN service provider 106 proceeds to identify a next closest destination POP among the remaining POPs. The CDN service provider 106 then adds to the aggregate spare capacity an estimated spare capacity of the newly identified destination POP and determines whether the updated aggregate spare capacity is sufficient to absorb the traffic surge. This process can be repeated many times until the aggregate spare capacity is sufficient.


In some embodiments, after all applicable destination POPs have been identified and corresponding spare capacity accounted for, the aggregate spare capacity may still be insufficient to absorb the traffic surge. In these embodiments, the CDN service provider 106 may cause routing of such surged traffic exclusively to a specific POP or set of POPs, thereby eliminating its impact on other POPs. Further, tarpitting or other network traffic control mechanisms can be implemented by the specific POP or set of POPs to ensure a certain level of service availability thereon.


At block 508, the CDN service provider 106 may cause routing of at least a portion of future traffic corresponding to the target resource group to identified destination POPs. Illustratively, the CDN service provider 106 may determine a policy or mechanism for routing incoming content requests for network resources corresponding to the target group, in accordance with the estimated spare capacities associated with the source POP and/or destination POPs. In some embodiments, the routing policy may correspond to a probabilistic or otherwise randomized decision scheme, where an incoming resource request is more likely to be routed to a POP associated with a larger spare capacity. The routing policy can be implemented for a future period of time, when at least some incoming requests for the target group will be routed to one of the destination POPs in accordance with the determined routing policy. The routine of FIG. 5 terminates at block 510.



FIG. 6 is a flowchart illustrative of a routine implemented by a CDN service provider 106 to conclude traffic surge mitigation. The routine starts at block 600. At block 602, while incoming traffic is routed in accordance with a traffic surge mitigation based routing policy or mechanism, the CDN service provider 106 determines an aggregate traffic volume for a resource group currently considered a target of traffic surge traffic. Illustratively, the CDN service provider 106 monitors request volumes for the target group received at the source and destination POPs as incoming traffic is routed during each time period. In doing so, the CDN service provider 106 may calculate an aggregate request volume for the target group based on respect volumes received at each applicable POP (e.g., by adding up respective request volumes received at each applicable POP during a most recent time period).


At block 604, the CDN service provider 106 decides whether to continue traffic surge mitigation based on the determined aggregate traffic volume. In some embodiments, the CDN service provider 106 may compare the aggregate traffic volume for a most recent time period to an estimated spare capacity of the source POP for the next time period, and determine whether the source POP may adequately process the aggregate volume (e.g., whether the source POP spare capacity exceeds the aggregate traffic volume by a predetermined margin). In some embodiments, the CDN service provider 106 may determine whether the aggregate traffic volume for a most recent period of time (or a weight average of aggregate volumes for a number of recent time periods) has returned to a level consistent with a traffic volume for the target group received at the source POP prior to the detection of traffic surge (e.g., not exceeding a maximum volume among a determined number of time periods prior to the detection of traffic surge).


If the CDN service provider 106 determines to continue the traffic surge mitigation, at block 606, the CDN service provider 106 causes adjustments to incoming traffic routing for the target group in a future time period based on the determined aggregate traffic volume. Similarly to relevant steps in the routine of FIG. 4, the CDN service provider 106 may determine whether a current aggregate spare capacity of the source and identified destination POPs is sufficient to absorb the aggregate traffic volume (e.g., whether the current aggregate spare capacity exceeds the aggregate traffic volume by a margin). If not, the CDN service provider 106 identifies additional destination POPs until the aggregate spare capacity is sufficient. In some embodiments, the CDN service provider 106 may remove one or more destination POPs currently in use, due to a surplus of aggregate spare capacity or other performance issues. Similarly to relevant steps in the routine of FIG. 4, in some embodiments, after all applicable destination POPs have been identified and corresponding spare capacity accounted for, the aggregate spare capacity may still be insufficient to absorb the aggregate traffic volume. In these embodiments, the CDN service provider 106 may cause routing of such traffic exclusively to a specific POP or set of POPs, thereby minimizing its impact on other POPs.


The CDN service provider 106 may modify the current policy or mechanism for routing incoming content requests for network resources corresponding to the target group, in accordance with currently estimated spare capacities associated with the source POP and/or destination POPs. The modified routing policy can be implemented for a future period of time, when at least some incoming requests for the target group will be routed to one of the destination POPs in accordance with the modified routing policy.


Referring back to block 604, if the CDN service provider 106 determines not to continue the mitigation, the routine of FIG. 6 proceeds to block 608. At block 608, the CDN service provider 106 causes a termination of the mitigation based incoming traffic routing for the target resource group. Illustratively, the CDN service provider 106 may cancel or deactivate relevant routing policies for offloading or spreading incoming traffic directed at the source POP for the target resource group. The routine of FIG. 6 ends at block 610.



FIG. 7 is an illustrative functional block diagram of a computing device for detecting and mitigating traffic surge. The computing device 700 can be a server or other computing device, and can comprise a processing unit 702, a network interface 704, a computer readable medium drive 706, an input/output device interface 708, and a memory 710. The network interface 704 can provide connectivity to one or more networks or computing systems. The processing unit 704 can receive information and instructions from other computing systems or services via the network interface 704. The network interface 704 can also store data directly to memory 710. The processing unit 702 can communicate to and from memory 710 and output information to an optional display 718 via the input/output device interface 708. The input/output device interface 708 can also accept input from the optional input device 720, such as a keyboard, mouse, digital pen, microphone, mass storage device, etc.


The memory 710 contains computer program instructions that the processing unit 702 executes in order to implement one or more embodiments. The memory 710 generally includes RAM, ROM, and/or other persistent, non-transitory computer readable media. The memory 710 can store an operating system 712 that provides computer program instructions for use by the processing unit 702 or other elements included in the computing device in the general administration and operation of the computing device 700. The memory 710 can further include computer program instructions and other information for implementing aspects of the present disclosure. For example, in one embodiment, the memory 710 includes traffic surge management software 714 that implements aspects of the present disclosure. The traffic surge management software 714 may illustratively correspond to all or some of the components of the request routing service 120, traffic surge detection service 130, traffic surge mitigation service 140 or other relevant components depicted in FIG. 1, or the illustrative routines of FIG. 4, 5 or 6.


The computing device 700 may further comprise traffic surge management hardware 730. The traffic surge management hardware 730 may illustratively implement aspects of the present disclosure, such as the components depicted in FIG. 1 or the illustrative routines of FIG. 4, 5 or 6. In some embodiments, the traffic surge hardware 730 may be implemented in part with the processing unit 702, the computer readable medium drive 706, or other elements of the computing device 700.


The elements included in the computing device 700 may be coupled by a bus 790. The bus 790 may be a data bus, communication bus, or other bus mechanism to enable the various components of the computing device 700 to exchange information. In some embodiments, the computing device 700 may include additional or fewer components than are shown in FIG. 7. For example, a computing device 700 may include more than one processing unit 702 and computer readable medium drive 706. In another example, the computing device 702 may not be coupled to a display 718 or an input device 720. In still another example, the traffic surge management software 714 or the traffic surge management hardware 730 may include various interdependent or independent subcomponents implementing different aspects of the present disclosure. In some embodiments, two or more computing devices 700 may together form a computer system for executing features of the present disclosure.


Depending on the embodiment, certain acts, events, or functions of any of the methods described herein can be performed in a different sequence, can be added, merged, or left out altogether (e.g., not all described acts or events are necessary for the practice of the algorithm). Moreover, in certain embodiments, acts or events can be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially.


The various illustrative logical blocks, modules and method elements described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.


The various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor can be a microprocessor, but in the alternative, the processor can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.


The elements of a method, process, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM or any other form of computer-readable storage medium known in the art. A storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components in a user terminal.


Conditional language used herein, such as, among others, “can,” “might,” “may,” “e.g.” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or states. Thus, such conditional language is not generally intended to imply that features, elements and/or states are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without author input or prompting, whether these features, elements and/or states are included or are to be performed in any particular embodiment. The terms “comprising,” “including,” “having,” “involving” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some or all of the elements in the list.


Disjunctive language such as the phrase “at least one of X, Y or Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y or Z, or any combination thereof (e.g., X, Y and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y or at least one of Z to each be present.


Unless otherwise explicitly stated, articles such as “a” or “an” should generally be interpreted to include one or more described items. Accordingly, phrases such as “a device configured to” are intended to include one or more recited devices. Such one or more recited devices can also be collectively configured to carry out the stated recitations. For example, “a processor configured to carry out recitations A, B and C” can include a first processor configured to carry out recitation A working in conjunction with a second processor configured to carry out recitations B and C.


While the above detailed description has shown, described, and pointed out novel features as applied to various embodiments, it will be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the spirit of the disclosure. As will be recognized, certain embodiments described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims
  • 1. A computer-implemented comprising: under control of one or more computing devices configured with specific computer executable instructions, obtaining first data that comprises requests for network resources received at a first point of presence (POP) during a first period of time, wherein the first data includes a first resource group, and wherein the first resource group is associated with a first request volume of network resource requests received at the first POP during the first period of time;comparing the first data to second data, wherein the second data comprises requests for network resources received at the first POP during a second period of time before the first period of time, wherein the second data includes the first resource group, and wherein the first resource group is associated with a second request volume quantifying network resource requests received at the first POP during the second period of time;determining that the first resource group is currently receiving flash crowd traffic based, at least in part, on the comparison between the first data and the second data; andgenerating a traffic increase alert corresponding to the first resource group.
  • 2. The computer-implemented method of claim 1, wherein the second period of time immediately precedes the first period of time.
  • 3. The computer-implemented method of claim 1, wherein the first resource group corresponds to at least one of a network page, a network application, a network site, a domain, or a sub-domain.
  • 4. The computer-implemented method of claim 1, wherein the first request volume associated with the first resource group is larger in quantity than the second request volume associated with the first resource group.
  • 5. The computer-implemented method of claim 1, wherein determining that the first resource group is currently receiving flash crowd traffic further comprises computing a difference or ratio between the first request volume associated with the first resource group and the second request volume associated with the first resource group.
  • 6. The computer-implemented method of claim 5, wherein determining that the first resource group is currently receiving flash crowd traffic further comprises determining that the difference or ratio satisfies a threshold criterion.
  • 7. The computer-implemented method of claim 6, wherein the threshold criterion is based, at least in part, on the second request volume associated with the first resource group.
  • 8. The computer-implemented method of claim 1, wherein determining that the first resource group is currently receiving flash crowd traffic is further based on a rate of change in request volume.
  • 9. A non-transitory computer readable storage medium storing computer executable instructions that, when executed, cause a computing device to: identify a first resource group, wherein the first resource group is associated with a first request volume for network resource requests received at a point of presence (POP) during a first period of time, wherein the first resource group is further associated with a second request volume for network resource requests received at the POP during a second period of time, and wherein the second period of time precedes the first period of time;determine that the first resource group is receiving an increase in traffic at the POP based, at least in part, on a difference between the first request volume and the second request volume; andgenerate an indication corresponding to the first resource group.
  • 10. The non-transitory computer readable storage medium of claim 9, wherein the computer executable instructions, when executed, further cause the computing device to identify the first resource group based, at least in part, on a ranking of the first resource group.
  • 11. The non-transitory computer readable storage medium of claim 10, wherein the computer executable instructions, when executed, further cause the computing device to determine that the ranking is higher than a threshold ranking.
  • 12. The non-transitory computer readable storage medium of claim 9, wherein the computer executable instructions, when executed, further cause the computing device to determine that the difference between the first request volume and second request volume is larger than a threshold value.
  • 13. The non-transitory computer readable storage medium of claim 9, wherein the second period of time and the first period of time correspond to consecutive time periods.
  • 14. The non-transitory computer readable storage medium of claim 9, wherein the first resource group is further associated with a third request volume quantifying network resource requests received at the POP during a third period of time, and wherein the third period of time precedes the second period of time.
  • 15. The non-transitory computer readable storage medium of claim 14, wherein the computer executable instructions, when executed, further cause the computing device to determine that the first resource group as receiving the increase in traffic based, at least in part, on a difference between the first request volume and the third request volume.
  • 16. A system comprising: at least one data store configured to at least store computer-executable instructions; anda processor in communication with the data store, the processor configured to execute the computer-executable instructions to at least: identify a first resource group, wherein the first resource group is associated with a first request volume quantifying network resource requests received at a point of presence (POP) during a first period of time, wherein the first resource group is further associated with a second request volume quantifying network resource requests received at the POP during a second period of time preceding the first period of time;determine that the first resource group is receiving an increase in traffic based, at least in part, on a difference between the first request volume and the second request volume; andgenerate an indication corresponding to the first resource group.
  • 17. The system of claim 16, wherein the computer-executable instructions further determine that the difference between the first request volume and second request volume is larger than a threshold value.
  • 18. The system of claim 17, wherein the first resource group is further associated with a third request volume quantifying network resource requests received at the POP during a third period of time, and wherein the third period of time precedes the second period of time.
  • 19. The system of claim 18, wherein the computer-executable instructions further determine that the first resource group as receiving the increase in traffic based, at least in part, on a difference between the first request volume and the third request volume.
  • 20. The system of claim 16, wherein the second period of time and the first period of time correspond to consecutive time periods.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 14/673,305, entitled “TRAFFIC SURGE MANAGEMENT FOR POINTS OF PRESENCE” and filed on Mar. 30, 2015, soon to issue as U.S. Pat. No. 9,819,567, which is hereby incorporated by reference herein in its entirety.

US Referenced Citations (1465)
Number Name Date Kind
5063500 Shorter Nov 1991 A
5341477 Pitkin et al. Aug 1994 A
5459837 Caccavale Oct 1995 A
5611049 Pitts Mar 1997 A
5701467 Freeston Dec 1997 A
5764910 Shachar Jun 1998 A
5774660 Brendel et al. Jun 1998 A
5852717 Bhide et al. Dec 1998 A
5892914 Pitts Apr 1999 A
5893116 Simmonds et al. Apr 1999 A
5895462 Toki Apr 1999 A
5905248 Russell et al. May 1999 A
5933811 Angles et al. Aug 1999 A
5937427 Shinagawa et al. Aug 1999 A
5974454 Apfel et al. Oct 1999 A
5991306 Burns et al. Nov 1999 A
5999274 Lee et al. Dec 1999 A
6006264 Colby et al. Dec 1999 A
6016512 Huitema Jan 2000 A
6018619 Allard et al. Jan 2000 A
6026452 Pitts Feb 2000 A
6038601 Lambert et al. Mar 2000 A
6052718 Gifford Apr 2000 A
6078960 Ballard Jun 2000 A
6085234 Pitts et al. Jul 2000 A
6092100 Berstis et al. Jul 2000 A
6098096 Tsirigotis et al. Aug 2000 A
6108703 Leighton et al. Aug 2000 A
6128279 O'Neil et al. Oct 2000 A
6151631 Ansell et al. Nov 2000 A
6157942 Chu et al. Dec 2000 A
6167438 Yates et al. Dec 2000 A
6167446 Lister et al. Dec 2000 A
6173316 De Boor et al. Jan 2001 B1
6182111 Inohara et al. Jan 2001 B1
6182125 Borella et al. Jan 2001 B1
6185598 Farber et al. Feb 2001 B1
6192051 Lipman et al. Feb 2001 B1
6205475 Pitts Mar 2001 B1
6223288 Byrne Apr 2001 B1
6243761 Mogul et al. Jun 2001 B1
6275496 Burns et al. Aug 2001 B1
6286043 Cuomo et al. Sep 2001 B1
6286084 Wexler et al. Sep 2001 B1
6304913 Rune Oct 2001 B1
6324580 Jindal et al. Nov 2001 B1
6330602 Law et al. Dec 2001 B1
6338082 Schneider Jan 2002 B1
6345308 Abe Feb 2002 B1
6351743 DeArdo et al. Feb 2002 B1
6351775 Yu Feb 2002 B1
6363411 Dugan et al. Mar 2002 B1
6366952 Pitts Apr 2002 B2
6374290 Scharber et al. Apr 2002 B1
6377257 Borrel et al. Apr 2002 B1
6386043 Millins May 2002 B1
6389532 Gupta et al. May 2002 B1
6405252 Gupta et al. Jun 2002 B1
6408360 Chamberlain et al. Jun 2002 B1
6411967 Van Renesse Jun 2002 B1
6415280 Farber et al. Jul 2002 B1
6430607 Kavner Aug 2002 B1
6438592 Killian Aug 2002 B1
6442165 Sitaraman et al. Aug 2002 B1
6452925 Sistanizadeh et al. Sep 2002 B1
6457047 Chandra et al. Sep 2002 B1
6459909 Bilcliff et al. Oct 2002 B1
6473804 Kaiser et al. Oct 2002 B1
6484143 Swildens et al. Nov 2002 B1
6484161 Chipalkatti et al. Nov 2002 B1
6493765 Cunningham et al. Dec 2002 B1
6505241 Pitts Jan 2003 B2
6513112 Craig et al. Jan 2003 B1
6523036 Hickman et al. Feb 2003 B1
6529910 Fleskes Mar 2003 B1
6529953 Van Renesse Mar 2003 B1
6553413 Leighton et al. Apr 2003 B1
6560610 Eatherton et al. May 2003 B1
6611873 Kanehara Aug 2003 B1
6622168 Datta Sep 2003 B1
6643357 Lumsden Nov 2003 B2
6643707 Booth Nov 2003 B1
6654807 Farber et al. Nov 2003 B2
6658462 Dutta Dec 2003 B1
6665706 Kenner et al. Dec 2003 B2
6678717 Schneider Jan 2004 B1
6678791 Jacobs et al. Jan 2004 B1
6681282 Golden et al. Jan 2004 B1
6687846 Adrangi et al. Feb 2004 B1
6694358 Swildens et al. Feb 2004 B1
6697805 Choquier et al. Feb 2004 B1
6718324 Edlund et al. Apr 2004 B2
6724770 Van Renesse Apr 2004 B1
6732237 Jacobs et al. May 2004 B1
6754699 Swildens et al. Jun 2004 B2
6754706 Swildens et al. Jun 2004 B1
6760721 Chasen et al. Jul 2004 B1
6769031 Bero Jul 2004 B1
6782398 Bahl Aug 2004 B1
6785704 McCanne Aug 2004 B1
6795434 Kumar et al. Sep 2004 B1
6799214 Li Sep 2004 B1
6804706 Pitts Oct 2004 B2
6810291 Card et al. Oct 2004 B2
6810411 Coughlin et al. Oct 2004 B1
6829654 Jungck Dec 2004 B1
6862607 Vermeulen Mar 2005 B1
6868439 Basu et al. Mar 2005 B2
6874017 Inoue et al. Mar 2005 B1
6917951 Orbits et al. Jul 2005 B2
6925499 Chen et al. Aug 2005 B1
6928467 Peng et al. Aug 2005 B2
6928485 Krishnamurthy et al. Aug 2005 B1
6941562 Gao et al. Sep 2005 B2
6950848 Yousefi'zadeh et al. Sep 2005 B1
6961783 Cook et al. Nov 2005 B1
6963850 Bezos et al. Nov 2005 B1
6976090 Ben-Shaul et al. Dec 2005 B2
6981017 Kasriel et al. Dec 2005 B1
6985945 Farhat et al. Jan 2006 B2
6986018 O'Rourke et al. Jan 2006 B2
6990526 Zhu Jan 2006 B1
6996616 Leighton et al. Feb 2006 B1
7003555 Jungck Feb 2006 B1
7006099 Gut et al. Feb 2006 B2
7007089 Freedman Feb 2006 B2
7010578 Lewin et al. Mar 2006 B1
7010598 Sitaraman et al. Mar 2006 B2
7024466 Outten et al. Apr 2006 B2
7027582 Khello et al. Apr 2006 B2
7031445 Lumsden Apr 2006 B2
7032010 Swildens et al. Apr 2006 B1
7058633 Gnagy et al. Jun 2006 B1
7058706 Iyer et al. Jun 2006 B1
7058953 Willard et al. Jun 2006 B2
7065587 Huitema et al. Jun 2006 B2
7072982 Teodosiu et al. Jul 2006 B2
7076633 Tormasov et al. Jul 2006 B2
7082476 Cohen et al. Jul 2006 B1
7086061 Joshi et al. Aug 2006 B1
7092505 Allison et al. Aug 2006 B2
7092997 Kasriel et al. Aug 2006 B1
7096266 Lewin et al. Aug 2006 B2
7099936 Chase et al. Aug 2006 B2
7103645 Leighton et al. Sep 2006 B2
7114160 Suryanarayana et al. Sep 2006 B2
7117262 Bai et al. Oct 2006 B2
7133905 Dilley Nov 2006 B2
7136922 Sundaram et al. Nov 2006 B2
7139808 Anderson et al. Nov 2006 B2
7139821 Shah et al. Nov 2006 B1
7143169 Champagne et al. Nov 2006 B1
7143170 Swildens et al. Nov 2006 B2
7146560 Dang et al. Dec 2006 B2
7149809 Barde et al. Dec 2006 B2
7152118 Anderson, IV et al. Dec 2006 B2
7162539 Garcie-Luna-Aceves Jan 2007 B2
7174382 Ramanathan et al. Feb 2007 B2
7185046 Ferstl et al. Feb 2007 B2
7185063 Kasriel et al. Feb 2007 B1
7185084 Sirivara et al. Feb 2007 B2
7188214 Kasriel et al. Mar 2007 B1
7194522 Swildens et al. Mar 2007 B1
7194552 Schneider Mar 2007 B1
7200667 Teodosiu et al. Apr 2007 B2
7216170 Ludvig et al. May 2007 B2
7225254 Swildens et al. May 2007 B1
7228350 Hong et al. Jun 2007 B2
7228359 Monteiro Jun 2007 B1
7233978 Overton et al. Jun 2007 B2
7240100 Wein et al. Jul 2007 B1
7249196 Peiffer et al. Jul 2007 B1
7251675 Kamakura et al. Jul 2007 B1
7254626 Kommula et al. Aug 2007 B1
7254636 O'Toole, Jr. et al. Aug 2007 B1
7257581 Steele et al. Aug 2007 B1
7260598 Liskov et al. Aug 2007 B1
7260639 Afergan et al. Aug 2007 B2
7269784 Kasriel et al. Sep 2007 B1
7272227 Beran Sep 2007 B1
7274658 Bornstein et al. Sep 2007 B2
7284056 Ramig Oct 2007 B2
7289519 Liskov Oct 2007 B1
7293093 Leighton Nov 2007 B2
7308499 Chavez Dec 2007 B2
7310686 Uysal Dec 2007 B2
7316648 Kelly et al. Jan 2008 B2
7318074 Iyengar et al. Jan 2008 B2
7320131 O'Toole, Jr. Jan 2008 B1
7321918 Burd et al. Jan 2008 B2
7337968 Wilz, Sr. et al. Mar 2008 B2
7339937 Mitra et al. Mar 2008 B2
7340505 Lisiecki et al. Mar 2008 B2
7350075 Eastham et al. Mar 2008 B1
7363291 Page Apr 2008 B1
7363626 Koutharapu et al. Apr 2008 B2
7370089 Boyd et al. May 2008 B2
7372809 Chen May 2008 B2
7373416 Kagan et al. May 2008 B2
7376716 Dilley May 2008 B2
7376736 Sundaram et al. May 2008 B2
7380078 Ikegaya et al. May 2008 B2
7389354 Sitaraman et al. Jun 2008 B1
7392236 Rusch et al. Jun 2008 B2
7398301 Hennessey et al. Jul 2008 B2
7406512 Swildens et al. Jul 2008 B2
7406522 Riddle Jul 2008 B2
7409712 Brooks et al. Aug 2008 B1
7430610 Pace et al. Sep 2008 B2
7441045 Skene et al. Oct 2008 B2
7441261 Slater et al. Oct 2008 B2
7451230 Corrado et al. Nov 2008 B2
7454457 Lowery et al. Nov 2008 B1
7454500 Hsu et al. Nov 2008 B1
7461170 Taylor et al. Dec 2008 B1
7464142 Flurry et al. Dec 2008 B2
7478148 Neerdaels Jan 2009 B2
7492720 Pruthi et al. Feb 2009 B2
7496651 Joshi Feb 2009 B1
7499998 Toebes et al. Mar 2009 B2
7502836 Menditto et al. Mar 2009 B1
7505464 Okmianski et al. Mar 2009 B2
7506034 Coates et al. Mar 2009 B2
7519720 Fishman et al. Apr 2009 B2
7519726 Palliyil et al. Apr 2009 B2
7523181 Swildens et al. Apr 2009 B2
7543024 Holstege Jun 2009 B2
7548947 Kasriel et al. Jun 2009 B2
7552235 Chase et al. Jun 2009 B2
7555542 Ayers et al. Jun 2009 B1
7561571 Lovett et al. Jul 2009 B1
7565407 Hayball Jul 2009 B1
7568032 Feng et al. Jul 2009 B2
7573916 Bechtolsheim et al. Aug 2009 B1
7574499 Swildens et al. Aug 2009 B1
7581009 Hsu et al. Aug 2009 B1
7593935 Sullivan Sep 2009 B2
7594189 Walker et al. Sep 2009 B1
7596619 Leighton et al. Sep 2009 B2
7603439 Dilley Oct 2009 B2
7613815 Prakash et al. Nov 2009 B1
7617222 Coulthard et al. Nov 2009 B2
7623460 Miyazaki Nov 2009 B2
7624169 Lisiecki et al. Nov 2009 B2
7631101 Sullivan et al. Dec 2009 B2
7640296 Fuchs et al. Dec 2009 B2
7650376 Blumenau Jan 2010 B1
7653700 Bahl et al. Jan 2010 B1
7653725 Yahiro et al. Jan 2010 B2
7657613 Hanson et al. Feb 2010 B1
7657622 Douglis et al. Feb 2010 B1
7661027 Langen et al. Feb 2010 B2
7664831 Cartmell et al. Feb 2010 B2
7664879 Chan et al. Feb 2010 B2
7676570 Levy et al. Mar 2010 B2
7680897 Carter et al. Mar 2010 B1
7684394 Cutbill et al. Mar 2010 B1
7685109 Ransil et al. Mar 2010 B1
7685251 Houlihan et al. Mar 2010 B2
7693813 Cao et al. Apr 2010 B1
7693959 Leighton et al. Apr 2010 B2
7702724 Brydon et al. Apr 2010 B1
7706740 Collins et al. Apr 2010 B2
7707314 McCarthy et al. Apr 2010 B2
7711647 Gunaseelan et al. May 2010 B2
7711788 Lev Ran et al. May 2010 B2
7716367 Leighton et al. May 2010 B1
7725602 Liu et al. May 2010 B2
7730187 Raciborski et al. Jun 2010 B2
7739400 Lindbo et al. Jun 2010 B2
7747720 Toebes et al. Jun 2010 B2
7756913 Day Jul 2010 B1
7756965 Joshi Jul 2010 B2
7757202 Dahlsted et al. Jul 2010 B2
7761572 Auerbach Jul 2010 B1
7765304 Davis et al. Jul 2010 B2
7769823 Jenny et al. Aug 2010 B2
7773596 Marques Aug 2010 B1
7774342 Virdy Aug 2010 B1
7783727 Foley et al. Aug 2010 B1
7787380 Aggarwal et al. Aug 2010 B1
7792989 Toebes et al. Sep 2010 B2
7805516 Kettler et al. Sep 2010 B2
7809597 Das et al. Oct 2010 B2
7813308 Reddy et al. Oct 2010 B2
7814229 Cabrera et al. Oct 2010 B1
7818454 Kim et al. Oct 2010 B2
7827256 Phillips et al. Nov 2010 B2
7836177 Kasriel et al. Nov 2010 B2
7853719 Cao et al. Dec 2010 B1
7865594 Baumback et al. Jan 2011 B1
7865953 Hsieh et al. Jan 2011 B1
7873065 Mukerji et al. Jan 2011 B1
7890612 Todd et al. Feb 2011 B2
7899899 Joshi Mar 2011 B2
7904875 Hegyi Mar 2011 B2
7912921 O'Rourke et al. Mar 2011 B2
7925782 Sivasubramanian et al. Apr 2011 B2
7930393 Baumback et al. Apr 2011 B1
7930402 Swildens et al. Apr 2011 B2
7930427 Josefsberg et al. Apr 2011 B2
7933988 Nasuto et al. Apr 2011 B2
7937477 Day et al. May 2011 B1
7945693 Farber et al. May 2011 B2
7949779 Farber et al. May 2011 B2
7958222 Pruitt et al. Jun 2011 B1
7958258 Yeung et al. Jun 2011 B2
7962597 Richardson et al. Jun 2011 B2
7966404 Hedin et al. Jun 2011 B2
7970816 Chess et al. Jun 2011 B2
7970940 van de Ven et al. Jun 2011 B1
7979509 Malmskog et al. Jul 2011 B1
7991910 Richardson et al. Aug 2011 B2
7996533 Leighton et al. Aug 2011 B2
7996535 Auerbach Aug 2011 B2
8000724 Rayburn et al. Aug 2011 B1
8001187 Stochosky Aug 2011 B2
8010707 Elzur et al. Aug 2011 B2
8019869 Kriegsman Sep 2011 B2
8024441 Kommula et al. Sep 2011 B2
8028090 Richardson et al. Sep 2011 B2
8041773 Abu-Ghazaleh et al. Oct 2011 B2
8041809 Sundaram et al. Oct 2011 B2
8041818 Gupta et al. Oct 2011 B2
8042054 White et al. Oct 2011 B2
8065275 Eriksen et al. Nov 2011 B2
8069231 Schran et al. Nov 2011 B2
8073940 Richardson et al. Dec 2011 B1
8082348 Averbuj et al. Dec 2011 B1
8108623 Krishnaprasad et al. Jan 2012 B2
8117306 Baumback et al. Feb 2012 B1
8122098 Richardson et al. Feb 2012 B1
8122124 Baumback et al. Feb 2012 B1
8132242 Wu Mar 2012 B1
8135820 Richardson et al. Mar 2012 B2
8155126 Mao et al. Apr 2012 B1
8156199 Hoche-Mong et al. Apr 2012 B1
8156243 Richardson et al. Apr 2012 B2
8175863 Ostermeyer et al. May 2012 B1
8190682 Paterson-Jones et al. May 2012 B2
8195605 Chellappa et al. Jun 2012 B2
8195837 McCarthy et al. Jun 2012 B2
8209695 Pruyne et al. Jun 2012 B1
8224971 Miller et al. Jul 2012 B1
8224986 Liskov et al. Jul 2012 B1
8224994 Schneider Jul 2012 B1
8234403 Richardson et al. Jul 2012 B2
8239530 Sundaram et al. Aug 2012 B2
8250135 Driesen et al. Aug 2012 B2
8250211 Swildens et al. Aug 2012 B2
8250219 Raciborski et al. Aug 2012 B2
8266288 Banerjee et al. Sep 2012 B2
8266327 Kumar et al. Sep 2012 B2
8271471 Kamvar et al. Sep 2012 B1
8280998 Joshi Oct 2012 B2
8281035 Farber et al. Oct 2012 B2
8291046 Farber et al. Oct 2012 B2
8291117 Eggleston et al. Oct 2012 B1
8296393 Alexander et al. Oct 2012 B2
8301600 Helmick et al. Oct 2012 B1
8301645 Crook Oct 2012 B1
8321568 Sivasubramanian et al. Nov 2012 B2
8356074 Ehrlich et al. Jan 2013 B1
8380831 Barber Feb 2013 B2
8380851 McCarthy et al. Feb 2013 B2
8392928 Forys et al. Mar 2013 B1
8402137 Sivasuramanian et al. Mar 2013 B2
8423408 Barnes et al. Apr 2013 B1
8423662 Weihl et al. Apr 2013 B1
8433749 Wee et al. Apr 2013 B2
8443167 Fallone et al. May 2013 B1
8447831 Sivasubramanian et al. May 2013 B1
8447876 Verma et al. May 2013 B2
8452745 Ramakrishna May 2013 B2
8452874 MacCarthaigh et al. May 2013 B2
8463877 Richardson Jun 2013 B1
8468222 Sakata et al. Jun 2013 B2
8468245 Farber et al. Jun 2013 B2
8473613 Farber et al. Jun 2013 B2
8478903 Farber et al. Jul 2013 B2
8504721 Hsu et al. Aug 2013 B2
8510428 Joshi Aug 2013 B2
8510807 Elazary et al. Aug 2013 B1
8521851 Richardson Aug 2013 B1
8521876 Goodman et al. Aug 2013 B2
8521880 Richardson et al. Aug 2013 B1
8521885 Richardson et al. Aug 2013 B1
8521908 Holmes et al. Aug 2013 B2
8526405 Curtis et al. Sep 2013 B2
8527639 Liskov et al. Sep 2013 B1
8527645 Proffit et al. Sep 2013 B1
8527658 Holmes et al. Sep 2013 B2
8549646 Stavrou et al. Oct 2013 B2
8572208 Farber et al. Oct 2013 B2
8572210 Farber et al. Oct 2013 B2
8577992 Richardson et al. Nov 2013 B1
8589996 Ma et al. Nov 2013 B2
8606996 Richardson et al. Dec 2013 B2
8612565 Schneider Dec 2013 B2
8615549 Knowles et al. Dec 2013 B2
8619780 Brandwine Dec 2013 B1
8626950 Richardson et al. Jan 2014 B1
8635340 Schneider Jan 2014 B1
8639817 Sivasubramanian et al. Jan 2014 B2
8645539 McCarthy et al. Feb 2014 B2
8645700 Smith et al. Feb 2014 B2
8676918 Richardson et al. Mar 2014 B2
8683023 Brandwine et al. Mar 2014 B1
8683076 Farber et al. Mar 2014 B2
8688837 Richardson et al. Apr 2014 B1
8712950 Smith et al. Apr 2014 B2
8732309 Richardson et al. May 2014 B1
8745177 Kazerani et al. Jun 2014 B1
8756322 Lynch Jun 2014 B1
8756325 Sivasubramanian et al. Jun 2014 B2
8756341 Richardson et al. Jun 2014 B1
8775553 Cansino et al. Jul 2014 B2
8782236 Marshall et al. Jul 2014 B1
8782279 Eggleston et al. Jul 2014 B2
8812727 Sorenson, III et al. Aug 2014 B1
8819283 Richardson et al. Aug 2014 B2
8826032 Yahalom et al. Sep 2014 B1
8904009 Marshall et al. Dec 2014 B1
8914514 Jenkins et al. Dec 2014 B1
8924528 Richardson et al. Dec 2014 B1
8930513 Richardson et al. Jan 2015 B1
8930544 Richardson et al. Jan 2015 B2
8935744 Osterweil et al. Jan 2015 B2
8938526 Richardson et al. Jan 2015 B1
8949161 Borst et al. Feb 2015 B2
8949459 Scholl Feb 2015 B1
8966318 Shah Feb 2015 B1
8972580 Fleischman et al. Mar 2015 B2
9003035 Richardson et al. Apr 2015 B1
9003040 MacCarthaigh et al. Apr 2015 B2
9009286 Sivasubramanian et al. Apr 2015 B2
9009334 Jenkins et al. Apr 2015 B1
9021127 Richardson et al. Apr 2015 B2
9021128 Sivasubramanian et al. Apr 2015 B2
9021129 Richardson et al. Apr 2015 B2
9026616 Sivasubramanian et al. May 2015 B2
9037975 Taylor et al. May 2015 B1
9075777 Pope et al. Jul 2015 B1
9075893 Jenkins Jul 2015 B1
9083675 Richardson et al. Jul 2015 B2
9083743 Patel et al. Jul 2015 B1
9106701 Richardson et al. Aug 2015 B2
9116803 Agrawal et al. Aug 2015 B1
9130756 Richardson et al. Sep 2015 B2
9130977 Zisapel et al. Sep 2015 B2
9137302 Makhijani et al. Sep 2015 B1
9154551 Watson Oct 2015 B1
9160703 Richardson et al. Oct 2015 B2
9172674 Patel et al. Oct 2015 B1
9176894 Marshall et al. Nov 2015 B2
9185012 Richardson et al. Nov 2015 B2
9191338 Richardson et al. Nov 2015 B2
9191458 Richardson et al. Nov 2015 B2
9195996 Walsh et al. Nov 2015 B1
9208097 Richardson et al. Dec 2015 B2
9210235 Sivasubramanian et al. Dec 2015 B2
9219686 Hilt Dec 2015 B2
9237087 Risbood et al. Jan 2016 B1
9237114 Richardson et al. Jan 2016 B2
9240954 Ellsworth et al. Jan 2016 B1
9246776 Ellsworth et al. Jan 2016 B2
9251112 Richardson et al. Feb 2016 B2
9253065 Richardson et al. Feb 2016 B2
9276812 Nagargadde et al. Mar 2016 B1
9294391 Mostert Mar 2016 B1
9323577 Marr et al. Apr 2016 B2
9332078 Sivasubramanian et al. May 2016 B2
9386038 Martini Jul 2016 B2
9391949 Richardson et al. Jul 2016 B1
9407676 Archer et al. Aug 2016 B2
9407681 Richardson et al. Aug 2016 B1
9407699 Sivasubramanian et al. Aug 2016 B2
9444718 Khakpour et al. Sep 2016 B2
9444759 Richardson et al. Sep 2016 B2
9479476 Richardson et al. Oct 2016 B2
9495338 Hollis et al. Nov 2016 B1
9497259 Richardson et al. Nov 2016 B1
9515949 Richardson et al. Dec 2016 B2
9525659 Sonkin et al. Dec 2016 B1
9544394 Richardson et al. Jan 2017 B2
9571389 Richardson et al. Feb 2017 B2
9584328 Graham-cumming Feb 2017 B1
9590946 Richardson et al. Mar 2017 B2
9608957 Sivasubramanian et al. Mar 2017 B2
9621660 Sivasubramanian et al. Apr 2017 B2
9628509 Holloway et al. Apr 2017 B2
9628554 Marshall et al. Apr 2017 B2
9645808 Turpie May 2017 B1
9703713 Nadgowda Jul 2017 B2
9705922 Foxhoven et al. Jul 2017 B2
9712325 Richardson et al. Jul 2017 B2
9712484 Richardson et al. Jul 2017 B1
9734472 Richardson et al. Aug 2017 B2
9742795 Radlein et al. Aug 2017 B1
9760420 Letz et al. Sep 2017 B1
9774619 Radlein et al. Sep 2017 B1
9787599 Richardson et al. Oct 2017 B2
9787775 Richardson et al. Oct 2017 B1
9794216 Richardson et al. Oct 2017 B2
9794281 Radlein et al. Oct 2017 B1
9800539 Richardson et al. Oct 2017 B2
9811451 Arguelles et al. Nov 2017 B1
9819567 Uppal et al. Nov 2017 B1
9832141 Raftery Nov 2017 B1
9871794 Joffe et al. Jan 2018 B2
9887914 Bergman Feb 2018 B2
9887915 Richardson et al. Feb 2018 B2
9887931 Uppal et al. Feb 2018 B1
9887932 Uppal et al. Feb 2018 B1
9888089 Sivasubramanian et al. Feb 2018 B2
9893957 Ellsworth et al. Feb 2018 B2
9894168 Sivasubramanian et al. Feb 2018 B2
9900402 Li et al. Feb 2018 B1
9912740 Richardson et al. Mar 2018 B2
9929959 Mostert Mar 2018 B2
9930131 MacCarthaigh et al. Mar 2018 B2
9954934 Sivasubramanian et al. Apr 2018 B2
9985927 Richardson et al. May 2018 B2
9992086 Mizik et al. Jun 2018 B1
9992303 Richardson et al. Jun 2018 B2
10015237 Richardson et al. Jul 2018 B2
10015241 Marr et al. Jul 2018 B2
10021179 Velummylum et al. Jul 2018 B1
10027582 Richardson et al. Jul 2018 B2
10033627 Howard et al. Jul 2018 B1
10033691 Mizik et al. Jul 2018 B1
10033699 Sullivan et al. Jul 2018 B2
10049051 Baldwin Aug 2018 B1
10075551 Baldwin et al. Sep 2018 B1
10079742 Richardson et al. Sep 2018 B1
10091096 Howard et al. Oct 2018 B1
10097398 Richardson et al. Oct 2018 B1
10097448 Howard et al. Oct 2018 B1
10097566 Radlein et al. Oct 2018 B1
10110694 Watson et al. Oct 2018 B1
10116584 Richardson et al. Oct 2018 B2
10135620 Richardson et al. Nov 2018 B2
10157135 Richardson et al. Dec 2018 B2
10158729 Sivasubramanian et al. Dec 2018 B2
10162753 Marshall et al. Dec 2018 B2
10180993 Raftery Jan 2019 B2
10200402 Radlein et al. Feb 2019 B2
10200492 MacCarthaigh et al. Feb 2019 B2
10205698 Petersen et al. Feb 2019 B1
10218584 Ellsworth et al. Feb 2019 B2
10225322 Richardson et al. Mar 2019 B2
10225326 Puchala et al. Mar 2019 B1
10225362 Watson Mar 2019 B2
10230819 Richardson et al. Mar 2019 B2
10257307 Baldwin Apr 2019 B1
10264062 Richardson et al. Apr 2019 B2
10270878 Uppal et al. Apr 2019 B1
10305797 Richardson et al. May 2019 B2
20010000811 May et al. May 2001 A1
20010025305 Yoshiasa et al. Sep 2001 A1
20010027479 Delaney et al. Oct 2001 A1
20010032133 Moran Oct 2001 A1
20010034704 Farhat et al. Oct 2001 A1
20010049741 Skene et al. Dec 2001 A1
20010052016 Skene et al. Dec 2001 A1
20010056416 Garcia-Luna-Aceves Dec 2001 A1
20010056500 Farber et al. Dec 2001 A1
20020002613 Freeman et al. Jan 2002 A1
20020004846 Garcia-Luna-Aceves et al. Jan 2002 A1
20020007413 Garcia-Luna-Aceves et al. Jan 2002 A1
20020010783 Primak et al. Jan 2002 A1
20020010798 Ben-Shaul et al. Jan 2002 A1
20020035624 Kim Mar 2002 A1
20020048269 Hong et al. Apr 2002 A1
20020049608 Hartsell et al. Apr 2002 A1
20020049842 Huetsch et al. Apr 2002 A1
20020049857 Farber et al. Apr 2002 A1
20020052942 Swildens et al. May 2002 A1
20020062372 Hong et al. May 2002 A1
20020065910 Dutta May 2002 A1
20020068554 Dusse Jun 2002 A1
20020069420 Russell et al. Jun 2002 A1
20020078233 Biliris et al. Jun 2002 A1
20020082858 Heddaya et al. Jun 2002 A1
20020083118 Sim Jun 2002 A1
20020083148 Shaw et al. Jun 2002 A1
20020083178 Brothers Jun 2002 A1
20020083198 Kim et al. Jun 2002 A1
20020087374 Boubez et al. Jul 2002 A1
20020091786 Yamaguchi et al. Jul 2002 A1
20020091801 Lewin et al. Jul 2002 A1
20020092026 Janniello et al. Jul 2002 A1
20020099616 Sweldens Jul 2002 A1
20020099850 Farber et al. Jul 2002 A1
20020101836 Dorenbosch Aug 2002 A1
20020103820 Cartmell et al. Aug 2002 A1
20020103972 Satran et al. Aug 2002 A1
20020107944 Bai et al. Aug 2002 A1
20020112049 Elnozahy et al. Aug 2002 A1
20020112123 Becker et al. Aug 2002 A1
20020116481 Lee Aug 2002 A1
20020116491 Boyd et al. Aug 2002 A1
20020116582 Copeland et al. Aug 2002 A1
20020120666 Landsman et al. Aug 2002 A1
20020120782 Dillon et al. Aug 2002 A1
20020124047 Gartner et al. Sep 2002 A1
20020124098 Shaw Sep 2002 A1
20020129123 Johnson et al. Sep 2002 A1
20020131428 Pecus et al. Sep 2002 A1
20020133741 Maeda et al. Sep 2002 A1
20020135611 Deosaran et al. Sep 2002 A1
20020138286 Engstrom Sep 2002 A1
20020138437 Lewin et al. Sep 2002 A1
20020138443 Schran et al. Sep 2002 A1
20020138649 Cartmell et al. Sep 2002 A1
20020143675 Orshan Oct 2002 A1
20020143798 Lisiecki et al. Oct 2002 A1
20020143989 Huitema et al. Oct 2002 A1
20020145993 Chowdhury et al. Oct 2002 A1
20020147770 Tang Oct 2002 A1
20020147774 Lisiecki et al. Oct 2002 A1
20020150094 Cheng et al. Oct 2002 A1
20020150276 Chang Oct 2002 A1
20020152326 Orshan Oct 2002 A1
20020154157 Sherr et al. Oct 2002 A1
20020156884 Bertram et al. Oct 2002 A1
20020156911 Croman et al. Oct 2002 A1
20020161745 Call Oct 2002 A1
20020161767 Shapiro et al. Oct 2002 A1
20020163882 Bornstein et al. Nov 2002 A1
20020165912 Wenocur et al. Nov 2002 A1
20020169890 Beaumont et al. Nov 2002 A1
20020184368 Wang Dec 2002 A1
20020188722 Banerjee et al. Dec 2002 A1
20020194324 Guha Dec 2002 A1
20020194382 Kausik et al. Dec 2002 A1
20020198953 O'Rourke et al. Dec 2002 A1
20030002484 Freedman Jan 2003 A1
20030004998 Datta Jan 2003 A1
20030005036 Mitzenmacher Jan 2003 A1
20030005111 Allan Jan 2003 A1
20030007482 Khello et al. Jan 2003 A1
20030009488 Hart, III Jan 2003 A1
20030009591 Hayball et al. Jan 2003 A1
20030026410 Lumsden Feb 2003 A1
20030028642 Agarwal et al. Feb 2003 A1
20030033283 Evans et al. Feb 2003 A1
20030037108 Peiffer et al. Feb 2003 A1
20030037139 Shteyn Feb 2003 A1
20030037284 Srinivasan et al. Feb 2003 A1
20030041094 Lara et al. Feb 2003 A1
20030046343 Krishnamurthy et al. Mar 2003 A1
20030065739 Shnier Apr 2003 A1
20030070096 Pazi et al. Apr 2003 A1
20030074401 Connell et al. Apr 2003 A1
20030074471 Anderson et al. Apr 2003 A1
20030074472 Lucco et al. Apr 2003 A1
20030079027 Slocombe et al. Apr 2003 A1
20030093523 Cranor et al. May 2003 A1
20030099202 Lear et al. May 2003 A1
20030099237 Mitra et al. May 2003 A1
20030101278 Garcia-Luna-Aceves et al. May 2003 A1
20030105829 Hayward Jun 2003 A1
20030105857 Kamen et al. Jun 2003 A1
20030112792 Cranor et al. Jun 2003 A1
20030120741 Wu et al. Jun 2003 A1
20030126387 Watanabe Jul 2003 A1
20030133554 Nykanen et al. Jul 2003 A1
20030135467 Okamoto Jul 2003 A1
20030135509 Davis et al. Jul 2003 A1
20030140087 Lincoln et al. Jul 2003 A1
20030145038 Bin Tariq et al. Jul 2003 A1
20030145066 Okada et al. Jul 2003 A1
20030149581 Chaudhri et al. Aug 2003 A1
20030154239 Davis et al. Aug 2003 A1
20030154284 Bernardin et al. Aug 2003 A1
20030163722 Anderson, IV Aug 2003 A1
20030172145 Nguyen Sep 2003 A1
20030172183 Anderson, IV et al. Sep 2003 A1
20030172291 Judge et al. Sep 2003 A1
20030174648 Wang et al. Sep 2003 A1
20030177321 Watanabe Sep 2003 A1
20030182305 Balva et al. Sep 2003 A1
20030182413 Allen et al. Sep 2003 A1
20030182447 Schilling Sep 2003 A1
20030187935 Agarwalla et al. Oct 2003 A1
20030187970 Chase et al. Oct 2003 A1
20030191822 Leighton et al. Oct 2003 A1
20030200394 Ashmore et al. Oct 2003 A1
20030204602 Hudson et al. Oct 2003 A1
20030206520 Wu et al. Nov 2003 A1
20030229682 Day Dec 2003 A1
20030233423 Dilley Dec 2003 A1
20030233445 Levy et al. Dec 2003 A1
20030233455 Leber et al. Dec 2003 A1
20030236700 Arning et al. Dec 2003 A1
20030236779 Choi et al. Dec 2003 A1
20040003032 Ma et al. Jan 2004 A1
20040010562 Itonaga Jan 2004 A1
20040010563 Forte et al. Jan 2004 A1
20040010588 Slater et al. Jan 2004 A1
20040010601 Afergan Jan 2004 A1
20040010621 Afergan et al. Jan 2004 A1
20040015584 Cartmell et al. Jan 2004 A1
20040019518 Abraham et al. Jan 2004 A1
20040024841 Becker et al. Feb 2004 A1
20040030620 Benjamin et al. Feb 2004 A1
20040032278 Orii et al. Feb 2004 A1
20040034744 Karlsson et al. Feb 2004 A1
20040039798 Hotz et al. Feb 2004 A1
20040044731 Chen et al. Mar 2004 A1
20040044791 Pouzzner Mar 2004 A1
20040054757 Ueda et al. Mar 2004 A1
20040059805 Dinker et al. Mar 2004 A1
20040064335 Yang Apr 2004 A1
20040064501 Jan et al. Apr 2004 A1
20040068542 Lalonde et al. Apr 2004 A1
20040073596 Kloninger et al. Apr 2004 A1
20040073707 Dillon Apr 2004 A1
20040073867 Kausik et al. Apr 2004 A1
20040078468 Hedin et al. Apr 2004 A1
20040078487 Cernohous et al. Apr 2004 A1
20040083283 Sundaram et al. Apr 2004 A1
20040083307 Uysal Apr 2004 A1
20040105544 Haneda et al. Jun 2004 A1
20040117309 Inoue et al. Jun 2004 A1
20040117455 Kaminksy et al. Jun 2004 A1
20040128344 Trossen Jul 2004 A1
20040128346 Melamed et al. Jul 2004 A1
20040148520 Talpade et al. Jul 2004 A1
20040167981 Douglas et al. Aug 2004 A1
20040167982 Cohen et al. Aug 2004 A1
20040170379 Yao et al. Sep 2004 A1
20040172466 Douglas et al. Sep 2004 A1
20040184456 Binding et al. Sep 2004 A1
20040194085 Beaubien et al. Sep 2004 A1
20040194102 Neerdaels Sep 2004 A1
20040203630 Wang Oct 2004 A1
20040205149 Dillon et al. Oct 2004 A1
20040205162 Parikh Oct 2004 A1
20040215823 Kleinfelter et al. Oct 2004 A1
20040221019 Swildens et al. Nov 2004 A1
20040221034 Kausik et al. Nov 2004 A1
20040246948 Lee et al. Dec 2004 A1
20040249939 Amini et al. Dec 2004 A1
20040249971 Klinker Dec 2004 A1
20040249975 Tuck et al. Dec 2004 A1
20040250119 Shelest et al. Dec 2004 A1
20040254921 Cohen et al. Dec 2004 A1
20040267906 Truty Dec 2004 A1
20040267907 Gustafsson Dec 2004 A1
20050010653 McCanne Jan 2005 A1
20050015471 Zhang et al. Jan 2005 A1
20050021706 Maggi et al. Jan 2005 A1
20050021862 Schroeder et al. Jan 2005 A1
20050027882 Sullivan et al. Feb 2005 A1
20050038967 Umbehocker et al. Feb 2005 A1
20050039019 Delany Feb 2005 A1
20050044270 Grove et al. Feb 2005 A1
20050102683 Branson et al. May 2005 A1
20050108169 Balasubramanian et al. May 2005 A1
20050108262 Fawcett May 2005 A1
20050108529 Juneau May 2005 A1
20050114296 Farber et al. May 2005 A1
20050117717 Lumsden Jun 2005 A1
20050132083 Raciborski et al. Jun 2005 A1
20050147088 Bao et al. Jul 2005 A1
20050149529 Gutmans Jul 2005 A1
20050157712 Rangarajan et al. Jul 2005 A1
20050160133 Greenlee et al. Jul 2005 A1
20050163168 Sheth et al. Jul 2005 A1
20050168782 Kobashi et al. Aug 2005 A1
20050171959 Deforche et al. Aug 2005 A1
20050172080 Miyauchi Aug 2005 A1
20050174989 Chen et al. Aug 2005 A1
20050181769 Kogawa Aug 2005 A1
20050188073 Nakamichi et al. Aug 2005 A1
20050192008 Desai et al. Sep 2005 A1
20050192814 Challener et al. Sep 2005 A1
20050198170 LeMay et al. Sep 2005 A1
20050198200 Subramanian et al. Sep 2005 A1
20050198303 Knauerhase et al. Sep 2005 A1
20050198334 Farber et al. Sep 2005 A1
20050198453 Osaki Sep 2005 A1
20050198571 Kramer et al. Sep 2005 A1
20050201302 Gaddis et al. Sep 2005 A1
20050216483 Armstrong et al. Sep 2005 A1
20050216569 Coppola et al. Sep 2005 A1
20050216674 Robbin et al. Sep 2005 A1
20050223095 Volz et al. Oct 2005 A1
20050228856 Swildens et al. Oct 2005 A1
20050229119 Torvinen Oct 2005 A1
20050232165 Brawn et al. Oct 2005 A1
20050234864 Shapiro Oct 2005 A1
20050240574 Challenger et al. Oct 2005 A1
20050256880 Nam Koong et al. Nov 2005 A1
20050259645 Chen et al. Nov 2005 A1
20050259672 Eduri Nov 2005 A1
20050262248 Jennings, III et al. Nov 2005 A1
20050266835 Agrawal et al. Dec 2005 A1
20050267928 Anderson et al. Dec 2005 A1
20050267937 Daniels et al. Dec 2005 A1
20050267991 Huitema et al. Dec 2005 A1
20050267992 Huitema et al. Dec 2005 A1
20050267993 Huitema et al. Dec 2005 A1
20050278259 Gunaseelan et al. Dec 2005 A1
20050283759 Peteanu et al. Dec 2005 A1
20050283784 Suzuki Dec 2005 A1
20050286564 Hatley et al. Dec 2005 A1
20060005014 Aura et al. Jan 2006 A1
20060013158 Ahuja et al. Jan 2006 A1
20060020596 Liu et al. Jan 2006 A1
20060020684 Mukherjee et al. Jan 2006 A1
20060020714 Girouard et al. Jan 2006 A1
20060020715 Jungck Jan 2006 A1
20060021001 Giles et al. Jan 2006 A1
20060026067 Nicholas et al. Feb 2006 A1
20060026154 Altinel et al. Feb 2006 A1
20060031239 Koenig Feb 2006 A1
20060031319 Nelson et al. Feb 2006 A1
20060031503 Gilbert Feb 2006 A1
20060034494 Holloran Feb 2006 A1
20060036720 Faulk, Jr. Feb 2006 A1
20060036966 Yevdayev Feb 2006 A1
20060037037 Miranz Feb 2006 A1
20060039352 Karstens Feb 2006 A1
20060041614 Oe Feb 2006 A1
20060045005 Blackmore et al. Mar 2006 A1
20060047787 Aggarwal et al. Mar 2006 A1
20060047813 Aggarwal et al. Mar 2006 A1
20060059246 Grove Mar 2006 A1
20060063534 Kokkonen et al. Mar 2006 A1
20060064476 Decasper et al. Mar 2006 A1
20060064500 Roth et al. Mar 2006 A1
20060070060 Tantawi et al. Mar 2006 A1
20060074750 Clark et al. Apr 2006 A1
20060075084 Lyon Apr 2006 A1
20060075139 Jungck Apr 2006 A1
20060083165 McLane et al. Apr 2006 A1
20060085536 Meyer et al. Apr 2006 A1
20060088026 Mazur et al. Apr 2006 A1
20060106938 Dini et al. May 2006 A1
20060107036 Randle et al. May 2006 A1
20060112066 Hamzy May 2006 A1
20060112176 Liu May 2006 A1
20060120385 Atchison et al. Jun 2006 A1
20060129665 Toebes et al. Jun 2006 A1
20060129766 Cassia et al. Jun 2006 A1
20060136453 Kwan Jun 2006 A1
20060143293 Freedman Jun 2006 A1
20060143442 Smith Jun 2006 A1
20060146820 Friedman et al. Jul 2006 A1
20060149529 Nguyen et al. Jul 2006 A1
20060155823 Tran et al. Jul 2006 A1
20060155862 Kathi et al. Jul 2006 A1
20060161541 Cencini Jul 2006 A1
20060165051 Banerjee et al. Jul 2006 A1
20060168088 Leighton et al. Jul 2006 A1
20060173957 Robinson Aug 2006 A1
20060179080 Meek et al. Aug 2006 A1
20060184936 Abels et al. Aug 2006 A1
20060188097 Taniguchi et al. Aug 2006 A1
20060190605 Franz et al. Aug 2006 A1
20060193247 Naseh et al. Aug 2006 A1
20060195866 Thukral Aug 2006 A1
20060206568 Verma et al. Sep 2006 A1
20060206586 Ling et al. Sep 2006 A1
20060218265 Farber et al. Sep 2006 A1
20060218304 Mukherjee et al. Sep 2006 A1
20060221971 Andrieux et al. Oct 2006 A1
20060224752 Parekh et al. Oct 2006 A1
20060227740 McLaughlin et al. Oct 2006 A1
20060227758 Rana et al. Oct 2006 A1
20060230137 Gare et al. Oct 2006 A1
20060230265 Krishna Oct 2006 A1
20060233155 Srivastava Oct 2006 A1
20060253546 Chang et al. Nov 2006 A1
20060253609 Andreev et al. Nov 2006 A1
20060259581 Piersol Nov 2006 A1
20060259690 Vittal et al. Nov 2006 A1
20060259984 Juneau Nov 2006 A1
20060265497 Ohata et al. Nov 2006 A1
20060265508 Angel et al. Nov 2006 A1
20060265516 Schilling Nov 2006 A1
20060265720 Cai et al. Nov 2006 A1
20060271641 Stavrakos et al. Nov 2006 A1
20060282522 Lewin et al. Dec 2006 A1
20060288119 Kim et al. Dec 2006 A1
20060288424 Saito Dec 2006 A1
20070005689 Leighton et al. Jan 2007 A1
20070005801 Kumar et al. Jan 2007 A1
20070005892 Mullender et al. Jan 2007 A1
20070011267 Overton et al. Jan 2007 A1
20070014241 Banerjee et al. Jan 2007 A1
20070021998 Laithwaite et al. Jan 2007 A1
20070028001 Phillips et al. Feb 2007 A1
20070038729 Sullivan et al. Feb 2007 A1
20070038994 Davis et al. Feb 2007 A1
20070041393 Westhead et al. Feb 2007 A1
20070043667 Qawami et al. Feb 2007 A1
20070043859 Ruul Feb 2007 A1
20070050522 Grove et al. Mar 2007 A1
20070050703 Lebel Mar 2007 A1
20070055764 Dilley Mar 2007 A1
20070061440 Sundaram et al. Mar 2007 A1
20070064610 Khandani Mar 2007 A1
20070076872 Juneau Apr 2007 A1
20070086429 Lawrence et al. Apr 2007 A1
20070094361 Hoynowski et al. Apr 2007 A1
20070101061 Baskaran et al. May 2007 A1
20070101377 Six et al. May 2007 A1
20070118667 McCarthy et al. May 2007 A1
20070118668 McCarthy et al. May 2007 A1
20070134641 Lieu Jun 2007 A1
20070156726 Levy Jul 2007 A1
20070156919 Potti et al. Jul 2007 A1
20070162331 Sullivan Jul 2007 A1
20070168336 Ransil et al. Jul 2007 A1
20070168517 Weller Jul 2007 A1
20070174426 Swildens et al. Jul 2007 A1
20070174442 Sherman et al. Jul 2007 A1
20070174490 Choi et al. Jul 2007 A1
20070183342 Wong et al. Aug 2007 A1
20070198982 Bolan et al. Aug 2007 A1
20070204107 Greenfield et al. Aug 2007 A1
20070208737 Li et al. Sep 2007 A1
20070219795 Park et al. Sep 2007 A1
20070220010 Ertugrul Sep 2007 A1
20070233705 Farber et al. Oct 2007 A1
20070233706 Farber et al. Oct 2007 A1
20070233846 Farber et al. Oct 2007 A1
20070233884 Farber et al. Oct 2007 A1
20070233896 Hilt Oct 2007 A1
20070243860 Aiello et al. Oct 2007 A1
20070244964 Challenger et al. Oct 2007 A1
20070245022 Olliphant et al. Oct 2007 A1
20070250467 Mesnik et al. Oct 2007 A1
20070250468 Pieper Oct 2007 A1
20070250560 Wein et al. Oct 2007 A1
20070250601 Amlekar et al. Oct 2007 A1
20070250611 Bhogal et al. Oct 2007 A1
20070253377 Janneteau et al. Nov 2007 A1
20070255843 Zubev Nov 2007 A1
20070263604 Tal Nov 2007 A1
20070266113 Koopmans et al. Nov 2007 A1
20070266311 Westphal Nov 2007 A1
20070266333 Cossey et al. Nov 2007 A1
20070270165 Poosala Nov 2007 A1
20070271375 Hwang Nov 2007 A1
20070271385 Davis et al. Nov 2007 A1
20070271560 Wahlert et al. Nov 2007 A1
20070271608 Shimizu et al. Nov 2007 A1
20070280197 Pearlman et al. Dec 2007 A1
20070280229 Kenney Dec 2007 A1
20070288588 Wein et al. Dec 2007 A1
20070291739 Sullivan et al. Dec 2007 A1
20070294419 Ulevitch Dec 2007 A1
20080005057 Ozzie et al. Jan 2008 A1
20080008089 Bornstein Jan 2008 A1
20080016233 Schneider Jan 2008 A1
20080025304 Venkataswami et al. Jan 2008 A1
20080037536 Padmanabhan et al. Feb 2008 A1
20080046550 Mazur et al. Feb 2008 A1
20080046596 Afergan et al. Feb 2008 A1
20080049615 Bugenhagen Feb 2008 A1
20080056207 Eriksson et al. Mar 2008 A1
20080065724 Seed et al. Mar 2008 A1
20080065745 Leighton et al. Mar 2008 A1
20080066072 Yurekli et al. Mar 2008 A1
20080071859 Seed et al. Mar 2008 A1
20080071987 Karn et al. Mar 2008 A1
20080072264 Crayford Mar 2008 A1
20080082551 Farber et al. Apr 2008 A1
20080082662 Dandliker et al. Apr 2008 A1
20080086434 Chesla Apr 2008 A1
20080086559 Davis et al. Apr 2008 A1
20080086574 Raciborski et al. Apr 2008 A1
20080092242 Rowley Apr 2008 A1
20080101358 Van Ewijk et al. May 2008 A1
20080103805 Shear et al. May 2008 A1
20080104268 Farber et al. May 2008 A1
20080109679 Wright et al. May 2008 A1
20080114829 Button et al. May 2008 A1
20080125077 Velazquez et al. May 2008 A1
20080126706 Newport et al. May 2008 A1
20080134043 Georgis et al. Jun 2008 A1
20080140800 Farber et al. Jun 2008 A1
20080147866 Stolorz et al. Jun 2008 A1
20080147873 Matsumoto Jun 2008 A1
20080155059 Hardin et al. Jun 2008 A1
20080155061 Afergan et al. Jun 2008 A1
20080155613 Benya et al. Jun 2008 A1
20080155614 Cooper et al. Jun 2008 A1
20080162667 Verma et al. Jul 2008 A1
20080162821 Duran et al. Jul 2008 A1
20080162843 Davis et al. Jul 2008 A1
20080172488 Jawahar et al. Jul 2008 A1
20080189437 Halley Aug 2008 A1
20080201332 Souders et al. Aug 2008 A1
20080215718 Stolorz et al. Sep 2008 A1
20080215730 Sundaram et al. Sep 2008 A1
20080215735 Farber et al. Sep 2008 A1
20080215747 Menon et al. Sep 2008 A1
20080215750 Farber et al. Sep 2008 A1
20080215755 Farber et al. Sep 2008 A1
20080222281 Dilley Sep 2008 A1
20080222291 Weller et al. Sep 2008 A1
20080222295 Robinson et al. Sep 2008 A1
20080222647 Taylor et al. Sep 2008 A1
20080228574 Stewart et al. Sep 2008 A1
20080228920 Souders et al. Sep 2008 A1
20080235383 Schneider Sep 2008 A1
20080235400 Slocombe et al. Sep 2008 A1
20080256087 Piironen et al. Oct 2008 A1
20080256175 Lee et al. Oct 2008 A1
20080263135 Olliphant Oct 2008 A1
20080270882 Rollins et al. Oct 2008 A1
20080275772 Suryanarayana et al. Nov 2008 A1
20080281946 Swildens et al. Nov 2008 A1
20080281950 Wald et al. Nov 2008 A1
20080288722 Lecoq et al. Nov 2008 A1
20080301670 Gouge et al. Dec 2008 A1
20080312766 Couckuyt Dec 2008 A1
20080319862 Golan et al. Dec 2008 A1
20080320123 Houlihan et al. Dec 2008 A1
20080320269 Houlihan et al. Dec 2008 A1
20090013063 Soman Jan 2009 A1
20090016236 Alcala et al. Jan 2009 A1
20090029644 Sue et al. Jan 2009 A1
20090031367 Sue Jan 2009 A1
20090031368 Ling Jan 2009 A1
20090031376 Riley et al. Jan 2009 A1
20090043900 Barber Feb 2009 A1
20090049098 Pickelsimer et al. Feb 2009 A1
20090063038 Shrivathsan et al. Mar 2009 A1
20090063704 Taylor et al. Mar 2009 A1
20090070533 Elazary et al. Mar 2009 A1
20090083228 Shatz et al. Mar 2009 A1
20090083279 Hasek Mar 2009 A1
20090086728 Gulati et al. Apr 2009 A1
20090086741 Zhang Apr 2009 A1
20090089869 Varghese Apr 2009 A1
20090094252 Wong et al. Apr 2009 A1
20090103707 McGary et al. Apr 2009 A1
20090106202 Mizrahi Apr 2009 A1
20090106381 Kasriel et al. Apr 2009 A1
20090112703 Brown Apr 2009 A1
20090125393 Hwang et al. May 2009 A1
20090125934 Jones et al. May 2009 A1
20090132368 Cotter et al. May 2009 A1
20090132640 Verma et al. May 2009 A1
20090132648 Swildens et al. May 2009 A1
20090138533 Iwasaki et al. May 2009 A1
20090138582 Turk May 2009 A1
20090144411 Winkler et al. Jun 2009 A1
20090144412 Ferguson et al. Jun 2009 A1
20090150926 Schlack Jun 2009 A1
20090157504 Braemer et al. Jun 2009 A1
20090157850 Gagliardi et al. Jun 2009 A1
20090158163 Stephens et al. Jun 2009 A1
20090164331 Bishop et al. Jun 2009 A1
20090164614 Christian et al. Jun 2009 A1
20090177667 Ramos et al. Jul 2009 A1
20090182815 Czechowski et al. Jul 2009 A1
20090182837 Rogers Jul 2009 A1
20090182945 Aviles et al. Jul 2009 A1
20090187575 DaCosta Jul 2009 A1
20090198817 Sundaram et al. Aug 2009 A1
20090204682 Jeyaseelan et al. Aug 2009 A1
20090210549 Hudson et al. Aug 2009 A1
20090228708 Trostle Sep 2009 A1
20090233623 Johnson Sep 2009 A1
20090241167 Moore Sep 2009 A1
20090248697 Richardson et al. Oct 2009 A1
20090248786 Richardson et al. Oct 2009 A1
20090248787 Sivasubramanian et al. Oct 2009 A1
20090248852 Fuhrmann et al. Oct 2009 A1
20090248858 Sivasubramanian et al. Oct 2009 A1
20090248893 Richardson et al. Oct 2009 A1
20090249222 Schmidt et al. Oct 2009 A1
20090253435 Olofsson Oct 2009 A1
20090254661 Fullagar et al. Oct 2009 A1
20090259588 Lindsay Oct 2009 A1
20090259971 Rankine et al. Oct 2009 A1
20090262741 Jungck et al. Oct 2009 A1
20090271498 Cable Oct 2009 A1
20090271577 Campana et al. Oct 2009 A1
20090271730 Rose et al. Oct 2009 A1
20090276771 Nickolov et al. Nov 2009 A1
20090279444 Ravindran et al. Nov 2009 A1
20090282038 Subotin et al. Nov 2009 A1
20090287750 Banavar et al. Nov 2009 A1
20090307307 Igarashi Dec 2009 A1
20090327489 Swildens et al. Dec 2009 A1
20090327517 Sivasubramanian et al. Dec 2009 A1
20090327914 Adar et al. Dec 2009 A1
20100005175 Swildens et al. Jan 2010 A1
20100011061 Hudson et al. Jan 2010 A1
20100011126 Hsu et al. Jan 2010 A1
20100020699 On Jan 2010 A1
20100023601 Lewin et al. Jan 2010 A1
20100023621 Ezolt et al. Jan 2010 A1
20100030662 Klein Feb 2010 A1
20100030914 Sparks et al. Feb 2010 A1
20100034470 Valencia-Campo et al. Feb 2010 A1
20100036944 Douglis et al. Feb 2010 A1
20100042725 Jeon et al. Feb 2010 A1
20100049862 Dixon Feb 2010 A1
20100057894 Glasser Mar 2010 A1
20100070603 Moss et al. Mar 2010 A1
20100070700 Borst et al. Mar 2010 A1
20100074268 Raza Mar 2010 A1
20100082320 Wood et al. Apr 2010 A1
20100082787 Kommula et al. Apr 2010 A1
20100088367 Brown et al. Apr 2010 A1
20100088405 Huang et al. Apr 2010 A1
20100095008 Joshi Apr 2010 A1
20100100629 Raciborski et al. Apr 2010 A1
20100103837 Jungck et al. Apr 2010 A1
20100106934 Calder et al. Apr 2010 A1
20100111059 Beppu et al. May 2010 A1
20100115133 Joshi May 2010 A1
20100115342 Shigeta et al. May 2010 A1
20100121953 Friedman et al. May 2010 A1
20100121981 Drako May 2010 A1
20100122069 Gonion May 2010 A1
20100125626 Lucas et al. May 2010 A1
20100125673 Richardson et al. May 2010 A1
20100125675 Richardson et al. May 2010 A1
20100131646 Drako May 2010 A1
20100138559 Sullivan et al. Jun 2010 A1
20100150155 Napierala Jun 2010 A1
20100161564 Lee et al. Jun 2010 A1
20100161565 Lee et al. Jun 2010 A1
20100161799 Maloo Jun 2010 A1
20100169392 Lev Ran et al. Jul 2010 A1
20100169452 Atluri et al. Jul 2010 A1
20100174811 Musiri et al. Jul 2010 A1
20100191854 Isci et al. Jul 2010 A1
20100192225 Ma et al. Jul 2010 A1
20100217801 Leighton et al. Aug 2010 A1
20100217856 Falkena Aug 2010 A1
20100223364 Wei Sep 2010 A1
20100226372 Watanabe Sep 2010 A1
20100228819 Wei Sep 2010 A1
20100257024 Holmes et al. Oct 2010 A1
20100257266 Holmes et al. Oct 2010 A1
20100257566 Matila Oct 2010 A1
20100268789 Yoo et al. Oct 2010 A1
20100268814 Cross et al. Oct 2010 A1
20100274765 Murphy et al. Oct 2010 A1
20100281482 Pike et al. Nov 2010 A1
20100293296 Hsu et al. Nov 2010 A1
20100293479 Rousso et al. Nov 2010 A1
20100299427 Joshi Nov 2010 A1
20100299438 Zimmerman et al. Nov 2010 A1
20100299439 McCarthy et al. Nov 2010 A1
20100306382 Cardosa et al. Dec 2010 A1
20100312861 Kolhi et al. Dec 2010 A1
20100318508 Brawer et al. Dec 2010 A1
20100322255 Hao et al. Dec 2010 A1
20100325365 Colglazier et al. Dec 2010 A1
20100332595 Fullagar et al. Dec 2010 A1
20110010244 Hatridge Jan 2011 A1
20110016214 Jackson Jan 2011 A1
20110029598 Arnold et al. Feb 2011 A1
20110040893 Karaoguz et al. Feb 2011 A1
20110051738 Xu Mar 2011 A1
20110055386 Middleton et al. Mar 2011 A1
20110055714 Vemulapalli et al. Mar 2011 A1
20110055921 Narayanaswamy et al. Mar 2011 A1
20110057790 Martin et al. Mar 2011 A1
20110058675 Brueck et al. Mar 2011 A1
20110072138 Canturk et al. Mar 2011 A1
20110072366 Spencer Mar 2011 A1
20110078000 Ma et al. Mar 2011 A1
20110078230 Sepulveda Mar 2011 A1
20110085654 Jana et al. Apr 2011 A1
20110087769 Holmes et al. Apr 2011 A1
20110096987 Morales et al. Apr 2011 A1
20110106949 Patel et al. May 2011 A1
20110113467 Agarwal et al. May 2011 A1
20110125894 Anderson et al. May 2011 A1
20110153938 Verzunov et al. Jun 2011 A1
20110153941 Spatscheck et al. Jun 2011 A1
20110154318 Oshins et al. Jun 2011 A1
20110154350 Doyle et al. Jun 2011 A1
20110161461 Niven-Jenkins Jun 2011 A1
20110166935 Armentrout et al. Jul 2011 A1
20110182290 Perkins Jul 2011 A1
20110191445 Dazzi Aug 2011 A1
20110191447 Dazzi et al. Aug 2011 A1
20110191449 Swildens et al. Aug 2011 A1
20110191459 Joshi Aug 2011 A1
20110196892 Xia Aug 2011 A1
20110208876 Richardson et al. Aug 2011 A1
20110208958 Stuedi et al. Aug 2011 A1
20110209064 Jorgensen et al. Aug 2011 A1
20110219120 Farber et al. Sep 2011 A1
20110219372 Agarwal et al. Sep 2011 A1
20110238501 Almeida Sep 2011 A1
20110238793 Bedare et al. Sep 2011 A1
20110239215 Sugai Sep 2011 A1
20110252142 Richardson et al. Oct 2011 A1
20110252143 Baumback et al. Oct 2011 A1
20110255445 Johnson et al. Oct 2011 A1
20110258049 Ramer et al. Oct 2011 A1
20110258614 Tamm Oct 2011 A1
20110270964 Huang et al. Nov 2011 A1
20110276623 Girbal Nov 2011 A1
20110296053 Medved et al. Dec 2011 A1
20110296370 Ferris et al. Dec 2011 A1
20110302304 Baumback et al. Dec 2011 A1
20110307533 Saeki Dec 2011 A1
20110320522 Endres et al. Dec 2011 A1
20110320559 Foti Dec 2011 A1
20120011190 Driesen et al. Jan 2012 A1
20120023090 Holloway et al. Jan 2012 A1
20120023226 Petersen et al. Jan 2012 A1
20120036238 Sundaram et al. Feb 2012 A1
20120041970 Ghosh et al. Feb 2012 A1
20120066360 Ghosh Mar 2012 A1
20120072600 Richardson et al. Mar 2012 A1
20120072608 Peters et al. Mar 2012 A1
20120078998 Son et al. Mar 2012 A1
20120079096 Cowan et al. Mar 2012 A1
20120079115 Richardson et al. Mar 2012 A1
20120014249 Mao et al. Apr 2012 A1
20120089700 Safruti et al. Apr 2012 A1
20120089972 Scheidel et al. Apr 2012 A1
20120096065 Suit et al. Apr 2012 A1
20120096166 Devarapalli et al. Apr 2012 A1
20120110515 Abramoff et al. May 2012 A1
20120117621 Kondamuru et al. May 2012 A1
20120124184 Sakata et al. May 2012 A1
20120131177 Brandt et al. May 2012 A1
20120136697 Peles et al. May 2012 A1
20120142310 Pugh et al. Jun 2012 A1
20120143688 Alexander Jun 2012 A1
20120159476 Ramteke et al. Jun 2012 A1
20120166516 Simmons et al. Jun 2012 A1
20120169646 Berkes et al. Jul 2012 A1
20120173760 Jog et al. Jul 2012 A1
20120179796 Nagaraj et al. Jul 2012 A1
20120179817 Bade et al. Jul 2012 A1
20120179839 Raciborski et al. Jul 2012 A1
20120198043 Hesketh et al. Aug 2012 A1
20120198071 Black et al. Aug 2012 A1
20120209942 Zehavi et al. Aug 2012 A1
20120224516 Stojanovski et al. Sep 2012 A1
20120226649 Kovacs et al. Sep 2012 A1
20120233329 Dickinson et al. Sep 2012 A1
20120233522 Barton et al. Sep 2012 A1
20120233668 Leafe et al. Sep 2012 A1
20120239725 Hartrick et al. Sep 2012 A1
20120246129 Rothschild et al. Sep 2012 A1
20120246257 Brown Sep 2012 A1
20120254961 Kim et al. Oct 2012 A1
20120257628 Bu et al. Oct 2012 A1
20120259954 McCarthy et al. Oct 2012 A1
20120278229 Vishwanathan et al. Nov 2012 A1
20120278831 van Coppenolle et al. Nov 2012 A1
20120303785 Sivasubramanian et al. Nov 2012 A1
20120303804 Sundaram et al. Nov 2012 A1
20120311648 Swildens et al. Dec 2012 A1
20120324089 Joshi Dec 2012 A1
20130003547 Motwani et al. Jan 2013 A1
20130003735 Chao et al. Jan 2013 A1
20130007100 Trahan et al. Jan 2013 A1
20130007101 Trahan et al. Jan 2013 A1
20130007102 Trahan et al. Jan 2013 A1
20130007241 Trahan et al. Jan 2013 A1
20130007273 Baumback et al. Jan 2013 A1
20130018945 Vendrow et al. Jan 2013 A1
20130019311 Swildens et al. Jan 2013 A1
20130034099 Hikichi et al. Feb 2013 A1
20130041872 Aizman et al. Feb 2013 A1
20130046869 Jenkins et al. Feb 2013 A1
20130046883 Lientz et al. Feb 2013 A1
20130054675 Jenkins et al. Feb 2013 A1
20130055374 Kustarz et al. Feb 2013 A1
20130067530 Spektor et al. Mar 2013 A1
20130073808 Puthalath et al. Mar 2013 A1
20130080420 Taylor et al. Mar 2013 A1
20130080421 Taylor et al. Mar 2013 A1
20130080576 Taylor et al. Mar 2013 A1
20130080577 Taylor et al. Mar 2013 A1
20130080623 Thireault Mar 2013 A1
20130080627 Kukreja et al. Mar 2013 A1
20130080636 Friedman et al. Mar 2013 A1
20130086001 Bhogal et al. Apr 2013 A1
20130111035 Alapati et al. May 2013 A1
20130117282 Mugali, Jr. et al. May 2013 A1
20130117849 Golshan et al. May 2013 A1
20130130221 Kortemeyer et al. May 2013 A1
20130133057 Yoon et al. May 2013 A1
20130151646 Chidambaram et al. Jun 2013 A1
20130191499 Ludin et al. Jul 2013 A1
20130198341 Kim Aug 2013 A1
20130212300 Eggleston et al. Aug 2013 A1
20130219020 McCarthy et al. Aug 2013 A1
20130227165 Liu Aug 2013 A1
20130246567 Green et al. Sep 2013 A1
20130254269 Sivasubramanian et al. Sep 2013 A1
20130254879 Chesla et al. Sep 2013 A1
20130263256 Dickinson et al. Oct 2013 A1
20130268616 Sakata et al. Oct 2013 A1
20130275549 Field et al. Oct 2013 A1
20130279335 Ahmadi Oct 2013 A1
20130305046 Mankovski et al. Nov 2013 A1
20130311583 Humphreys et al. Nov 2013 A1
20130311605 Richardson et al. Nov 2013 A1
20130311989 Ota et al. Nov 2013 A1
20130339429 Richardson et al. Dec 2013 A1
20130346465 Maltz et al. Dec 2013 A1
20130346470 Obstfeld et al. Dec 2013 A1
20130346567 Richardson et al. Dec 2013 A1
20130346614 Baughman et al. Dec 2013 A1
20140006577 Joe et al. Jan 2014 A1
20140007239 Sharpe et al. Jan 2014 A1
20140013403 Shuster Jan 2014 A1
20140019605 Boberg Jan 2014 A1
20140022951 Lemieux Jan 2014 A1
20140036675 Wang et al. Feb 2014 A1
20140040478 Hsu et al. Feb 2014 A1
20140047104 Rodriguez Feb 2014 A1
20140053022 Forgette et al. Feb 2014 A1
20140059198 Richardson et al. Feb 2014 A1
20140059379 Ren et al. Feb 2014 A1
20140082165 Marr et al. Mar 2014 A1
20140082614 Klein et al. Mar 2014 A1
20140089917 Attalla et al. Mar 2014 A1
20140108672 Ou et al. Apr 2014 A1
20140122698 Batrouni et al. May 2014 A1
20140122725 Batrouni et al. May 2014 A1
20140137111 Dees et al. May 2014 A1
20140149601 Carney et al. May 2014 A1
20140164817 Bartholomy et al. Jun 2014 A1
20140165061 Greene et al. Jun 2014 A1
20140195686 Yeager et al. Jul 2014 A1
20140200036 Egner et al. Jul 2014 A1
20140215019 Ahrens Jul 2014 A1
20140244937 Bloomstein et al. Aug 2014 A1
20140269371 Badea et al. Sep 2014 A1
20140280606 Long Sep 2014 A1
20140280679 Dey et al. Sep 2014 A1
20140297866 Ennaji et al. Oct 2014 A1
20140297870 Eggleston et al. Oct 2014 A1
20140298021 Kwon et al. Oct 2014 A1
20140310402 Giaretta et al. Oct 2014 A1
20140310811 Hentunen Oct 2014 A1
20140325155 Marshall et al. Oct 2014 A1
20140331328 Wang et al. Nov 2014 A1
20140337472 Newton et al. Nov 2014 A1
20140351413 Smith et al. Nov 2014 A1
20140351871 Bomfim et al. Nov 2014 A1
20150006615 Wainner et al. Jan 2015 A1
20150019686 Backholm Jan 2015 A1
20150026407 Mclellan et al. Jan 2015 A1
20150067171 Yum Mar 2015 A1
20150074228 Drake Mar 2015 A1
20150081877 Sethi et al. Mar 2015 A1
20150088964 Shiell et al. Mar 2015 A1
20150088972 Brand et al. Mar 2015 A1
20150089621 Khalid Mar 2015 A1
20150106864 Li et al. Apr 2015 A1
20150154051 Kruglick Jun 2015 A1
20150156279 Vaswani et al. Jun 2015 A1
20150172379 Richardson et al. Jun 2015 A1
20150172407 MacCarthaigh et al. Jun 2015 A1
20150172414 Richardson et al. Jun 2015 A1
20150172415 Richardson et al. Jun 2015 A1
20150188734 Petrov Jul 2015 A1
20150189042 Sun et al. Jul 2015 A1
20150200991 Kwon Jul 2015 A1
20150207733 Richardson et al. Jul 2015 A1
20150215656 Pulung et al. Jul 2015 A1
20150229710 Sivasubramanian et al. Aug 2015 A1
20150244580 Saavedra Aug 2015 A1
20150256647 Richardson et al. Sep 2015 A1
20150288647 Chhabra et al. Oct 2015 A1
20150319260 Watson Nov 2015 A1
20150341431 Hartrick et al. Nov 2015 A1
20150358276 Liu et al. Dec 2015 A1
20150358436 Kim et al. Dec 2015 A1
20150363113 Rahman et al. Dec 2015 A1
20150363282 Rangasamy Dec 2015 A1
20160006672 Saavedra Jan 2016 A1
20160021197 Pogrebinsky et al. Jan 2016 A1
20160026568 Marshall et al. Jan 2016 A1
20160028598 Khakpour et al. Jan 2016 A1
20160028755 Vasseur et al. Jan 2016 A1
20160036857 Foxhoven et al. Feb 2016 A1
20160041910 Richardson et al. Feb 2016 A1
20160065475 Hilt Mar 2016 A1
20160065665 Richardson et al. Mar 2016 A1
20160072669 Saavedra Mar 2016 A1
20160072720 Richardson et al. Mar 2016 A1
20160104346 Ovalle Apr 2016 A1
20160132600 Woodhead et al. May 2016 A1
20160134492 Ellsworth et al. May 2016 A1
20160142251 Contreras et al. May 2016 A1
20160182454 Phonsa et al. Jun 2016 A1
20160182542 Staniford Jun 2016 A1
20160205062 Mosert Jul 2016 A1
20160241637 Marr et al. Aug 2016 A1
20160241639 Brookins et al. Aug 2016 A1
20160253262 Nadgowda Sep 2016 A1
20160255042 Newton Sep 2016 A1
20160269927 Kim et al. Sep 2016 A1
20160274929 King Sep 2016 A1
20160294678 Khakpour et al. Oct 2016 A1
20160308959 Richardson et al. Oct 2016 A1
20160337426 Shribman et al. Nov 2016 A1
20160366202 Phillips et al. Dec 2016 A1
20170041428 Katsev Feb 2017 A1
20170099345 Leach Apr 2017 A1
20170109316 Hack et al. Apr 2017 A1
20170126557 Richardson et al. May 2017 A1
20170126796 Hollis et al. May 2017 A1
20170142062 Richardson et al. May 2017 A1
20170153980 Araújo et al. Jun 2017 A1
20170155678 Araújo et al. Jun 2017 A1
20170155732 Araújo et al. Jun 2017 A1
20170163425 Kaliski, Jr. Jun 2017 A1
20170171146 Sharma et al. Jun 2017 A1
20170180217 Puchala et al. Jun 2017 A1
20170180267 Puchala et al. Jun 2017 A1
20170214755 Sivasubramanian et al. Jul 2017 A1
20170214761 Hsu et al. Jul 2017 A1
20170250821 Richardson et al. Aug 2017 A1
20170257340 Richardson et al. Sep 2017 A1
20170353395 Richardson et al. Dec 2017 A1
20180063027 Rafferty Mar 2018 A1
20180077109 Hoeme et al. Mar 2018 A1
20180077110 Huston, III et al. Mar 2018 A1
20180097631 Uppal et al. Apr 2018 A1
20180097634 Uppal et al. Apr 2018 A1
20180097831 Uppal et al. Apr 2018 A1
20180109553 Radlein et al. Apr 2018 A1
20180159769 Richardson et al. Jun 2018 A1
20180167444 Sivasubramanian et al. Jun 2018 A1
20180167469 Sivasubramanian et al. Jun 2018 A1
20180173526 Prinsloo et al. Jun 2018 A1
20180183689 Ellsworth et al. Jun 2018 A1
20180191817 Richardson et al. Jul 2018 A1
20180212880 Mostert Jul 2018 A1
20180213052 Maccarthaigh et al. Jul 2018 A1
20180278717 Richardson et al. Sep 2018 A1
20180287916 Mizik et al. Oct 2018 A1
20180302322 Richardson et al. Oct 2018 A1
20180332107 Marr et al. Nov 2018 A1
20180351904 Mizik et al. Dec 2018 A1
20180367498 Bliss et al. Dec 2018 A1
20190007515 Baldwin et al. Jan 2019 A1
20190020562 Richardson et al. Jan 2019 A1
20190028562 Watson et al. Jan 2019 A1
20190044787 Richardson et al. Feb 2019 A1
20190044846 Howard et al. Feb 2019 A1
20190073303 Marshall et al. Mar 2019 A1
20190089542 Richardson et al. Mar 2019 A1
20190098109 Watson Mar 2019 A1
20190121739 Richardson et al. Apr 2019 A1
20190129908 Kumarasamy May 2019 A1
20190140922 Ellsworth et al. May 2019 A1
Foreign Referenced Citations (41)
Number Date Country
2741 895 May 2010 CA
1422468 Jun 2003 CN
1511399 Jul 2004 CN
1605182 Apr 2005 CN
101189598 May 2008 CN
101460907 Jun 2009 CN
103731481 Apr 2014 CN
1603307 Dec 2005 EP
1351141 Oct 2007 EP
2008167 Dec 2008 EP
3156911 Apr 2017 EP
07-141305 Jun 1995 JP
2001-0506093 May 2001 JP
2001-249907 Sep 2001 JP
2002-024192 Jan 2002 JP
2002-044137 Feb 2002 JP
2002-323986 Nov 2002 JP
2003-167810 Jun 2003 JP
2003-167813 Jun 2003 JP
2003-188901 Jul 2003 JP
2003-522358 Jul 2003 JP
2004-070935 Mar 2004 JP
2004-532471 Oct 2004 JP
2004-533738 Nov 2004 JP
2005-537687 Dec 2005 JP
2007-133896 May 2007 JP
2007-207225 Aug 2007 JP
2008-515106 May 2008 JP
2009-071538 Apr 2009 JP
2012-509623 Apr 2012 JP
2012-209623 Oct 2012 JP
WO 2002069608 Sep 2002 WO
WO 2005071560 Aug 2005 WO
WO 2007007960 Jan 2007 WO
WO 2007126837 Nov 2007 WO
WO 2009124006 Oct 2009 WO
WO 2010002603 Jan 2010 WO
WO 2012044587 Apr 2012 WO
WO 2012065641 May 2012 WO
WO 2014047073 Mar 2014 WO
WO 2017106455 Jun 2017 WO
Non-Patent Literature Citations (175)
Entry
Office Action in Application No. 09729072.0 dated May 14, 2018.
Examination Report in Indian Application No. 6213/CHENP/2010 dated May 23, 2018.
International Preliminary Report on Patentability in PCT/US/2016/ 066848 dated Jun. 19, 2018.
“Non-Final Office Action dated Jan. 3, 2012,” U.S. Appl. No. 12/652,541; dated Jan. 3, 2012; 35 pages.
“Final Office Action dated Sep. 5, 2012,” U.S. Appl. No. 12/652,541; dated Sep. 5, 2012; 40 pages.
“Notice of Allowance dated Jan. 4, 2013,” U.S. Appl. No. 12/652,541; dated Jan. 4, 2013; 11 pages.
“Non-Final Office Action dated Apr. 30, 2014,” U.S. Appl. No. 13/842,970; 20 pages.
“Final Office Action dated Aug. 19, 2014,” U.S. Appl. No. 13/842,970; 13 pages.
“Notice of Allowance dated Dec. 5, 2014,” U.S. Appl. No. 13/842,970; 6 pages.
Canonical Name (CNAME) DNS Records, domainavenue.com, Feb. 1, 2001, XP055153783, Retrieved from the Internet: URL:http://www.domainavenue.com/cname.htm [retrieved on Nov. 18, 2014].
“Content delivery network”, Wikipedia, the free encyclopedia, Retrieved from the Internet: URL:http://en.wikipedia.org/w/index.php?title=Contentdelivery network&oldid=601009970, XP055153445, Mar. 24, 2008.
“Global Server Load Balancing with ServerIron,” Foundry Networks, retrieved Aug. 30, 2007, from http://www.foundrynet.com/pdf/an-global-server-load-bal.pdf, 7 pages.
“Grid Computing Solutions,” Sun Microsystems, Inc., retrieved May 3, 2006, from http://www.sun.com/software/grid, 3 pages.
“Grid Offerings,” Java.net, retrieved May 3, 2006, from http://wiki.java.net/bin/view/Sungrid/OtherGridOfferings, 8 pages.
“Recent Advances Boost System Virtualization,” eWeek.com, retrieved from May 3, 2006, http://www.eWeek.com/article2/0, 1895, 1772626,00.asp, 5 pages.
“Scaleable Trust of Next Generation Management (STRONGMAN),” retrieved May 17, 2006, from http://www.cis.upenn.edu/˜dsl/STRONGMAN/, 4 pages.
“Sun EDA Compute Ranch,” Sun Microsystems, Inc., retrieved May 3, 2006, from http://sun.com/processors/ranch/brochure.pdf, 2 pages.
“Sun Microsystems Accelerates UltraSP ARC Processor Design Program With New Burlington, Mass. Compute Ranch,” Nov. 6, 2002, Sun Microsystems, Inc., retrieved May 3, 2006, from http://www.sun.com/smi/Press/sunflash/2002-11/sunflash.20021106.3 .xml, 2 pages.
“Sun N1 Grid Engine 6,” Sun Microsystems, Inc., retrieved May 3, 2006, from http://www.sun.com/software/gridware/index.xml, 3 pages.
“Sun Opens New Processor Design Compute Ranch,” Nov. 30, 2001, Sun Microsystems, Inc., retrieved May 3, 2006, from http://www.sun.com/smi/Press/sunflash/2001-11/sunflash.2001-1130.1.xml, 3 pages.
“The Softricity Desktop,” Softricity, Inc., retrieved May 3, 2006, from http://www.softricity.com/products/, 3 pages.
“Xen—The Xen virtual Machine Monitor,” University of Cambridge Computer Laboratory, retrieved Nov. 8, 2005, from http://www.cl.cam.ac.uk/Research/SRG/netos/xen/, 2 pages.
“XenFaq,” retrieved Nov. 8, 2005, from http://wiki.xensource.com/xenwiki/XenFaq?action=print, 9 pages.
Abi, Issam, et al., “A Business Driven Management Framework for Utility Computing Environments,” Oct. 12, 2004, HP Laboratories Bristol, HPL-2004-171, retrieved Aug. 30, 2007, from http://www.hpl.hp.com/techreports/2004/HPL-2004-171.pdf, 14 pages.
American Bar Association; Digital Signature Guidelines Tutorial [online]; Feb. 10, 2002 [retrieved on Mar. 2, 2010]; American Bar Association Section of Science and Technology Information Security Committee; Retrieved from the internet: (URL: http://web.archive.org/web/20020210124615/www.abanet.org/scitech/ec/isc/dsg-tutorial.html; pp. 1-8.
Armour et al.: “A Heuristic Algorithm and Simulation Approach to Relative Location of Facilities”; Management Science, vol. 9, No. 2 (Jan. 1963); pp. 294-309.
Baglioni et al., “Preprocessing and Mining Web Log Data for Web Personalization”, LNAI 2829, 2003, pp. 237-249.
Barbir, A., et al., “Known Content Network (CN) Request-Routing Mechanisms”, Request for Comments 3568, [online], IETF, Jul. 2003, [retrieved on Feb. 26, 2013], Retrieved from the Internet: (URL: http://tools.ietf.org/rfc/rfc3568.txt).
Bellovin, S., “Distributed Firewalls,” ;login;:37-39, Nov. 1999, http://www.cs.columbia.edu/-smb/papers/distfw. html, 10 pages, retrieved Nov. 11, 2005.
Blaze, M., “Using the KeyNote Trust Management System,” Mar. 1, 2001, from http://www.crypto.com/trustmgt/kn.html, 4 pages, retrieved May 17, 2006.
Brenton, C., “What is Egress Filtering and How Can I Implement It?—Egress Filtering v 0.2,” Feb. 29, 2000, SANS Institute, http://www.sans.org/infosecFAQ/firewall/egress.htm, 6 pages.
Byun et al., “A Dynamic Grid Services Deployment Mechanism for On-Demand Resource Provisioning”, IEEE International Symposium on Cluster Computing and the Grid:863-870, 2005.
Chipara et al, “Realtime Power-Aware Routing in Sensor Network”, IEEE, 2006, 10 pages.
Clark, C., “Live Migration of Virtual Machines,” May 2005, NSDI '05: 2nd Symposium on Networked Systems Design and Implementation, Boston, MA, May 2-4, 2005, retrieved from http://www.usenix.org/events/nsdi05/tech/full_papers/clark/clark.pdf, 14 pages.
Coulson, D., “Network Security Iptables,” Apr. 2003, Linuxpro, Part 2, retrieved from http://davidcoulson.net/writing/lxf/38/iptables.pdf, 4 pages.
Coulson, D., “Network Security Iptables,” Mar. 2003, Linuxpro, Part 1, retrieved from http://davidcoulson.net/writing/lxf/39/iptables.pdf, 4 pages.
Deleuze, C., et al., A DNS Based Mapping Peering System for Peering CDNs, draft-deleuze-cdnp-dnsmap-peer-00.txt, Nov. 20, 2000, 20 pages.
Demers, A., “Epidemic Algorithms for Replicated Database Maintenance,” 1987, Proceedings of the sixth annual ACM Symposium on Principles of Distributed Computing, Vancouver, British Columbia, Canada, Aug. 10-12, 1987, 12 pages.
Gruener, J., “A Vision of Togetherness,” May 24, 2004, NetworkWorld, retrieved May 3, 2006, from, http://www.networkworld.com/supp/2004/ndc3/0524virt.html, 9 pages.
Gunther et al, “Measuring Round Trip Times to determine the Distance between WLAN Nodes”,May 2005, In Proc. of Networking 2005, all pages.
Gunther et al, “Measuring Round Trip Times to determine the Distance between WLAN Nodes”, Dec. 18, 2004, Technical University Berlin, all pages.
Guo, F., Understanding Memory Resource Management in Vmware vSphere 5.0, Vmware, 2011, pp. 1-29.
Hameed, CC, “Disk Fragmentation and System Performance”, Mar. 14, 2008, 3 pages.
Hartung et al.; Digital rights management and watermarking of multimedia content for m-commerce applications; Published in: Communications Magazine, IEEE (vol. 38, Issue: 11 ); Date of Publication: Nov. 2000; pp. 78-84; IEEE Xplore.
Horvath et al., “Enhancing Energy Efficiency in Multi-tier Web Server Clusters via Prioritization,” in Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International , vol., No., pp. 1-6, Mar. 26-30, 2007.
Ioannidis, S., et al., “Implementing a Distributed Firewall,” Nov. 2000, (ACM) Proceedings of the ACM Computer and Communications Security (CCS) 2000, Athens, Greece, pp. 190-199, retrieved from http://www.cis.upenn.edu/˜dls/STRONGMAN/Papers/dtpdf, 10 pages.
Joseph, Joshy, et al., “Introduction to Grid Computing,” Apr. 16, 2004, retrieved Aug. 30, 2007, from http://www.informit.com/articles/printerfriendly.aspx?p=169508, 19 pages.
Kalafut et al., Understanding Implications of DNS Zone Provisioning., Proceeding IMC '08 Proceedings of the 8th AMC SIGCOMM conference on Internet measurement., pp. 211-216., ACM New York, NY, USA., 2008.
Kato, Yoshinobu , Server load balancer—Difference in distribution technique and supported protocol—Focus on function to meet the needs, Nikkei Communications, Japan, Nikkei Business Publications, Inc., Mar. 20, 2000, vol. 314, pp. 114 to 123.
Kenshi, P., “Help File Library: Iptables Basics,” Justlinux, retrieved Dec. 1, 2005, from http://www.justlinux.com/nhf/Security/Iptables _ Basics.html, 4 pages.
Liu, “The Ultimate Guide to Preventing DNS-based DDoS Attacks”, Retrieved from http://www.infoworld.com/article/2612835/security/the-ultimate-guide-to-preventing-dns-based-ddos-attacks.html, Published Oct. 30, 2013.
Liu et al., “Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting users' future requests,” Data & Knowledge Engineering 61 (2007) pp. 304-330.
Maesono, et al., “A Local Scheduling Method considering Data Transfer in Data Grid,” Technical Report of IEICE, vol. 104, No. 692, pp. 435-440, The Institute of Electronics, Information and Communication Engineers, Japan, Feb. 2005.
Meng et al., “Improving the Scalability of Data Center Networks with Traffic-Aware Virtual Machine Placement”; Proceedings of the 29th Conference on Information Communications, INFOCOM'10, pp. 1154-1162. Piscataway, NJ. IEEE Press, 2010.
Mulligan et al.; How DRM-based content delivery systems disrupt expectations of “personal use”; Published in: Proceeding DRM '03 Proceedings of the 3rd ACM workshop on Digital rights management; 2003; pp. 77-89; ACM Digital Library.
Ragan, “Three Types of DNS Attacks and How to Deal with Them”, Retrieved from http://www.csoonline.com/article/2133916/malware-cybercrime/three-types-of-dns-attacks-and-how-to-deal-with-them.html, Published Aug. 28, 2013.
Shankland, S., “Sun to buy start-up to bolster N1 ,” Jul. 30, 2003, CNet News.com, retrieved May 3, 2006, http://news.zdnet.com/2100-3513_22-5057752.html, 8 pages.
Sharif et al, “Secure In-VM Monitoring Using Hardware Virtualization”, Microsoft, Oct. 2009 http://research.microsoft.com/pubs/153179/sim-ccs09.pdf; 11 pages.
Strand, L., “Adaptive distributed firewall using intrusion detection,” Nov. 1, 2004, University of Oslo Department of Informatics, retrieved Mar. 8, 2006, from http://gnist.org/˜lars/studies/master/StrandLars-master.pdf, 158 pages.
Takizawa, et al., “Scalable MultiReplication Framework on The Grid,” Report of Study of Information Processing Society of Japan, Information Processing Society, vol. 2004, No. 81, pp. 247-252, Japan, Aug. 1, 2004.
Tan et al., “Classification: Basic Concepts, Decision Tree, and Model Evaluation”, Introduction in Data Mining; http://www-users.cs.umn.edu/˜kumar/dmbook/ch4.pdf, 2005, pp. 245-205.
Van Renesse, R., “Astrolabe: A Robust and Scalable Technology for Distributed System Monitoring, Management, and Data Mining,” May 2003, ACM Transactions on Computer Systems (TOCS), 21 (2): 164-206, 43 pages.
Vijayan, J., “Terraspring Gives Sun's N1 a Boost,” Nov. 25, 2002, Computerworld, retrieved May 3, 2006, from http://www.computerworld.com/printthis/2002/0,4814, 76159,00.html, 3 pages.
Virtual Iron Software Home, Virtual Iron, retrieved May 3, 2006, from http://www.virtualiron.com/, 1 page.
Waldspurger, CA., “Spawn: A Distributed Computational Economy,” Feb. 1992, IEEE Transactions on Software Engineering, 18(2): 103-117, 15 pages.
Watanabe, et al., “Remote Program Shipping System for GridRPC Systems,” Report of Study of Information Processing Society of Japan, Information Processing Society, vol. 2003, No. 102, pp. 7378, Japan, Oct. 16, 2003.
Xu et al., “Decision tree regression for soft classification of remote sensing data”, Remote Sensing of Environment 97 (2005) pp. 322-336.
Yamagata, et al., “A virtual-machine based fast deployment tool for Grid execution environment,” Report of Study of Information Processing Society of Japan, Information Processing Society, vol. 2006, No. 20, pp. 127-132, Japan, Feb. 28, 2006.
Zhu, Xiaoyun, et al., “Utility-Driven Workload Management Using Nested Control Design,” Mar. 29, 2006, HP Laboratories Palo Alto, HPL-2005-193(R.1), retrieved Aug. 30, 2007, from http://www.hpl.hp.com/techreports/2005/HPL-2005-193R1.pdf, 9 pages.
Supplementary European Search Report in Application No. 09729072.0 2266064 dated Dec. 10, 2014.
First Singapore Written Opinion in Application No. 201006836-9, dated Oct. 12, 2011 in 12 pages.
Singapore Written Opinion in Application No. 201006836-9, dated Apr. 30, 2012 in 10 pages.
First Office Action in Chinese Application No. 200980111422.3 dated Apr. 13, 2012.
First Office Action in Japanese Application No. 2011-502138 dated Feb. 1, 2013.
Singapore Written Opinion in Application No. 201006837-7, dated Oct. 12, 2011 in 11 pages.
Supplementary European Search Report in Application No. 09727694.3 dated Jan. 30, 2012 in 6 pages.
Singapore Examination Report in Application No. 201006837-7 dated Mar. 16, 2012.
First Office Action in Chinese Application No. 200980111426.1 dated Feb. 16, 2013.
Second Office Action in Chinese Application No. 200980111426.1 dated Dec. 25, 2013.
Third Office Action in Chinese Application No. 200980111426.1 dated Jul. 7, 2014.
Fourth Office Action in Chinese Application No. 200980111426.1 dated Jan. 15, 2015.
Fifth Office Action in Chinese Application No. 200980111426.1 dated Aug. 14, 2015.
First Office Action in Japanese Application No. 2011-502139 dated Nov. 5, 2013.
Decision of Rejection in Application No. 2011-502139 dated Jun. 30, 2014.
Office Action in Japanese Application No. 2011-502139 dated Aug. 17, 2015.
Singapore Written Opinion in Application No. 201006874-0, dated Oct. 12, 2011 in 10 pages.
First Office Action in Japanese Application No. 2011-502140 dated Dec. 7, 2012.
First Office Action in Chinese Application No. 200980119995.0 dated Jul. 6, 2012.
Second Office Action in Chinese Application No. 200980119995.0 dated Apr. 15, 2013.
Examination Report in Singapore Application No. 201006874-0 dated May 16, 2012.
Search Report in European Application No. 09839809.2 dated May 11, 2015.
Office Action in European Application No. 09839809.2 dated Dec. 8, 2016.
Supplementary European Search Report in Application No. 09728756.9 dated Jan. 8, 2013.
First Office Action in Chinese Application No. 200980119993.1 dated Jul. 4, 2012.
Second Office Action in Chinese Application No. 200980119993.1 dated Mar. 12, 2013.
Third Office Action in Chinese Application No. 200980119993.1 dated Oct. 21, 2013.
First Office Action in Japanese Application No. 2011-503091 dated Nov. 18, 2013.
Office Action in Japanese Application No. 2014-225580 dated Oct. 26, 2015.
Office Action in Japanese Application No. 2014-225580 dated Oct. 3, 2016.
Search Report and Written Opinion issued in Singapore Application No. 201006873-2 dated Oct. 12, 2011.
First Office Action is Chinese Application No. 200980125551.8 dated Jul. 4, 2012.
First Office Action in Japanese Application No. 2011-516466 dated Mar. 6, 2013.
Second Office Action in Japanese Application No. 2011-516466 dated Mar. 17, 2014.
Decision of Refusal in Japanese Application No. 2011-516466 dated Jan. 16, 2015.
Office Action in Japanese Application No. 2011-516466 dated May 30, 2016.
Office Action in Japanese Application No. 2011-516466 dated Mar. 6, 2017.
Office Action in Canadian Application No. 2726915 dated May 13, 2013.
First Office Action in Korean Application No. 10-2011-7002461 dated May 29, 2013.
First Office Action in Chinese Application No. 200980145872.4 dated Nov. 29, 2012.
First Office Action in Canadian Application No. 2741895 dated Feb. 25, 2013.
Second Office Action in Canadian Application No. 2741895 dated Oct. 21, 2013.
Partial Supplementary Search Report in European Application No. 09826977.2 dated Oct. 4, 2016.
Search Report and Written Opinion in Singapore Application No. 201103333-9 dated Nov. 19, 2012.
Examination Report in Singapore Application No. 201103333-9 dated Aug. 13, 2013.
Office Action in Chinese Application No. 201310717573.1 dated Jul. 29, 2016.
Office Action in European Application No. 11767118.0 dated Feb. 3, 2017.
International Search Report and Written Opinion in PCT/US2011/053302 dated Nov. 28, 2011 in 11 pages.
International Preliminary Report on Patentability in PCT/US2011/053302 dated Apr. 2, 2013.
First Office Action in Japanese Application No. 2013-529454 dated Feb. 3, 2014 in 6 pages.
Office Action in Japanese Application No. 2013-529454 dated Mar. 9, 2015 in 8 pages.
First Office Action issued in Australian Application No. 2011307319 dated Mar. 6, 2014 in 5 pages.
Search Report and Written Opinion in Singapore Application No. 201301573-0 dated Jul. 1, 2014.
First Office Action in Chinese Application No. 201180046104.0 dated Nov. 3, 2014.
Second Office Action in Chinese Application No. 201180046104.0 dated Sep. 29, 2015.
Third Office Action in Chinese Application No. 201180046104.0 dated Apr. 14, 2016.
Decision of Rejection in Chinese Application No. 201180046104.0 dated Oct. 17, 2016.
Examination Report in Singapore Application No. 201301573-0 dated Dec. 22, 2014.
International Preliminary Report on Patentability in PCT/US2011/061486 dated May 22, 2013.
International Search Report and Written Opinion in PCT/US2011/061486 dated Mar. 30, 2012 in 11 pages.
Office Action in Canadian Application No. 2816612 dated Nov. 3, 2015.
Office Action in Canadian Application No. 2816612 dated Oct. 7, 2016.
Office Action in Canadian Application No. 2816612 dated Aug. 8, 2017.
First Office Action in Chinese Application No. 201180053405.6 dated Feb. 10, 2015.
Second Office Action in Chinese Application No. 201180053405.6 dated Dec. 4, 2015.
Office Action in Japanese Application No. 2013-540982 dated Jun. 2, 2014.
Written Opinion in Singapore Application No. 201303521-7 dated May 20, 2014.
Office Action in Japanese Application No. 2015-533132 dated Apr. 25, 2016.
Office Action in Canadian Application No. 2884796 dated Apr. 28, 2016.
Office Action in Russian Application No. 2015114568 dated May 16, 2016.
Supplementary Examination Report in Singapore Application No. 11201501987U dated May 17, 2017.
International Search Report and Written Opinion in PCT/US07/07601 dated Jul. 18, 2008 in 11 pages.
International Preliminary Report on Patentability in PCT/US2007/007601 dated Sep. 30, 2008 in 8 pages.
Supplementary European Search Report in Application No. 07754164.7 dated Dec. 20, 2010 in 7 pages.
Office Action in Chinese Application No. 200780020255.2 dated Mar. 4, 2013.
Office Action in Indian Application No. 3742/KOLNP/2008 dated Nov. 22, 2013.
Office Action in Japanese Application No. 2012-052264 dated Dec. 11, 2012 in 26 pages.
Office Action in Japanese Application No. 2013-123086 dated Apr. 15, 2014 in 3 pages.
Office Action in Japanese Application No. 2013-123086 dated Dec. 2, 2014 in 4 pages.
Office Action in Japanese Application No. 2015-075644 dated Apr. 5, 2016.
Office Action in European Application No. 07754164.7 dated Dec. 14, 2015.
Office Action in Chinese Application No. 201310537815.9 dated Jul. 5, 2016.
Office Action in Chinese Application No. 201310537815.9 dated Jun. 2, 2017.
International Search Report and Written Opinion in PCT/US/2016/ 066848 dated May 1, 2017.
Arends et al., DNS Security Introduction and Requirements, RFC 4033, Mar. 2005, 21 pages.
Ariyapperuma et al., “Security Vulnerabilities in DNS and DNSSEC.” The Second International Conference on Availability, Reliability and Security, IEEE, 2007, 8 pages.
Chandramouli et al., “Challenges in Securing the Domain Name System.” IEEE Security & Privacy4.1 (2006),pp. 84-87.
Eastlake, Donald, Domain Name System Security Extensions, RFC 2535, Mar. 1999, 47 pages.
Krsul et al., “VMPlants: Providing and Managing Virtual Machine Execution Environments for Grid Computing”, Nov. 6, 2004 (Nov. 6, 2004), Supercomputing, 2004. Proceedings of the ACM/IEEE SC2004 Conference Pittsburgh, PA, USA Nov. 6-12, 2004, Piscataway, NJ, USA, IEEE, 1730 Massachusetts Ave., NW Washington, DC 20036-1992 USA, 12 pages.
Zhao et al., “Distributed file system support for virtual machines in grid computing”, Jun. 4, 2004 (Jun. 4, 2004), High Performance Distributed Computing, 2004. Proceedings. 13th IEEE International Symposium on Honolulu, HI, USA Jun. 4-6, 2004, Piscataway, NJ, USA, IEEE, p. 202-211.
Office Action in Indian Application No. 5937/CHENP/2010 dated Jan. 19, 2018.
Office Action in Indian Application No. 6210/CHENP/2010 dated Mar. 27, 2018.
Office Action in Chinese Application No. 201310537815.9 dated Feb. 1, 2018.
Office Action in European Application No. 07754164.7 dated Jan. 25, 2018.
International Search Report and Written Opinion in PCT/US2017/055156 dated Dec. 13, 2017.
Cohen et al., “Proactive Caching of DNS Records: Addressing a Performance Bottleneck”, Proceedings of Saint 2001 Symposium on Applications and the Internet; 8-12, Jan. 8, 2001, IEEE Computer Society, pp. 85-94.
JH Software, Moving a DNS Server to a New IP Address, last updated Jan. 26, 2006, 1 page.
Office Action in European Application No. 11767118.0 dated Jul. 25, 2018.
Extended Search Report in European Application No. 18156163 dated Sep. 3, 2018.
Office Action in Chinese Application No. 2013800492635 dated Aug. 30, 2017.
Office Action in European Application No. 11767118.0 dated Jan. 29, 2019.
Examination Report in Indian Application No. 3105/DELNP/2013, dated Feb. 19, 2019.
Office Action in European Application No. 13770602.4 dated Mar. 11, 2019.
International Preliminary Report on Patentability and Written Opinion in PCT/US2017/055156 dated Apr. 9, 2019.
Office Action in Application No. 09729072.0 dated Dec. 7, 2018.
Examination Report in Indian Application No. 4487/DELNP/2013 dated Dec. 28, 2018.
Related Publications (1)
Number Date Country
20180159757 A1 Jun 2018 US
Continuations (1)
Number Date Country
Parent 14673305 Mar 2015 US
Child 15811437 US