The present technology pertains to operations and management of a data center environment which utilizes blade switches and blade servers on which containers providing microservices are deployed.
Microservices and containers have been gaining traction in the new age of application development coupled with, for example, container integration (CI)/continuous deployment (CD) model. One prevalent example standard of this system is provided by Docker. Containers have introduced new challenges to data centers in areas of provisioning, monitoring, manageability and scale. Monitoring and analytics tools are key asks from IT and data center operators to help the operators understand the network usage especially with the set of hybrid workloads present within a data center.
Typically, orchestration tools (e.g., Kubernetes, Swarm, Mesos etc.) are used for deploying containers. On the other hand, discovering and visualizing the container workloads on the servers is achieved by (1) listening to container events (start, stop etc.) from the container orchestrators along with associated metadata as to what container is running what application, the IP, the MAC, the image etc. and (2) gleaning physical connectivity via link discovery protocols (e.g., link layer discovery protocol (LLDP)/Cisco discovery protocol (CDP)) from the server and leaf (top of the rack (ToR)) switches. A Data Center controller like Data Center Network Manager (DCNM) already has the Data Center (DC) fabric topology information and therefore, visualizing the container workloads is a matter of correlating the connectivity information with the physical topology.
However, the above discovery and visualization process is inadequate in case of deployment of blade switches within a DC that sits between a blade server and leaf switches or ToRs. This is due to the fact that a blade switch consumes the LLDP/CDP frames and thus the connectivity information of a blade server (and consequently containers running on such blade server) to a network leaf will become invisible and cannot be gleaned easily. Therefore, it is not possible to determine information about container deployments across blade servers within a data center environment that connect to leaf switches within a fabric of a data center via one or more blade switches.
In order to describe the manner in which the above-recited and other advantages and features of the disclosure can be obtained, a more particular description of the principles briefly described above will be rendered by reference to specific examples thereof which are illustrated in the appended drawings. Understanding that these drawings depict only examples of the disclosure and are not therefore to be considered to be limiting of its scope, the principles herein are described and explained with additional specificity and detail through the use of the accompanying drawings in which:
Overview
In one aspect of the present disclosure, a method of determining container to leaf switch connectivity information of a data center utilizing at least one blade switch and at least one blade server, includes receiving, at a network controller, link connectivity information that includes south-bound neighboring information between the at least one blade switch of the data center and the at least one blade server of the data center; determining, at the network controller, the container to leaf switch connectivity information a the data center, based on the link connectivity information, and generating a visual representation of a topology of the data center based on the container to leaf switch connectivity information.
In one aspect of the present disclosure, a data center includes at least one blade switch; at least one blade server; and at least one network controller configured to receive link connectivity inform ad on that includes south-bound neighboring information between the at least one blade switch of the data center and the at least one blade server of the data center; determine container to leaf switch connectivity information of the data center based on the link connectivity information; and generate a visual representation of a topology of the data center based on the container to leaf switch connectivity information.
In one aspect of the present disclosure, a non-transitory computer-readable medium has computer-readable instruction stored therein, which when executed by a processor, causes the processor to determine container to leaf switch connectivity information of a data center utilizing at least one blade switch and at least one blade server, by receiving link connectivity information that includes south-bound neighboring information between the at least one blade switch of the data center and the at least one blade server of the data center; determining, at the network controller, the container to leaf switch connectivity information of the data center, based on the link connectivity information; and generating a visual representation of a topology of the data center based on the container to leaf switch connectivity information.
Various examples of the disclosure are discussed in detail below. While specific implementations are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components and configurations may be used without parting from the spirit and scope of the disclosure.
References to one or an example embodiment in the present disclosure can be, but not necessarily are, references to the same example embodiment; and, such references mean at least one of the example embodiments.
Reference to “in one example embodiment” or an example embodiment means that a particular feature, structure, or characteristic described in connection with the example embodiment is included in at least one example of the disclosure. The appearances of the phrase “in one example embodiment” in various places in the specification are not necessarily all referring to the same example embodiment, nor are separate or alternative example embodiments mutually exclusive of other example embodiments. Moreover, various features are described which may be exhibited by some example embodiments and not by others. Similarly, various features are described which may be features for some example embodiments but not other example embodiments.
The terms used in this specification generally have their ordinary meanings in the art, within the context of the disclosure and in the specific context where each term is used. Alternative language and synonyms may be used for any one or more of the terms discussed herein, and no special significance should be placed upon whether or not a term is elaborated or discussed herein. Synonyms for certain terms are provided. A recital of one or more synonyms does not exclude the use of other synonyms. The use of examples anywhere in this specification including examples of any terms discussed herein is illustrative only, and is not intended to further limit the scope and meaning of the disclosure or of any exemplified term. Likewise, the disclosure is not limited to various examples given in this specification.
Without intent to limit the scope of the disclosure, examples of instruments, apparatus, methods and their related results according to examples of the present disclosure are given below. Note that titles or subtitles may be used in the examples for convenience of a reader, which in no way should limit the scope of the disclosure. Unless otherwise defined, technical and scientific terms used herein have the meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In the case of conflict, the present document, including definitions will control.
Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of this disclosure. As used herein, the term “and/or,” includes any and all combinations of one or more of the associated listed items.
When an element is referred to as being “connected,” or “coupled,” to another element, it can be directly connected or coupled to the other element or intervening elements may be present. By contrast, when an element is referred to as being “directly connected,” or “directly coupled,” to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a like fashion (e.g., “between,” versus “directly between,” “adjacent,” versus “directly adjacent,” etc.).
The terminology used herein is for the purpose of describing particular examples only and is not intended to be limiting. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises”, “comprising,”, “includes” and/or “including”, when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
Specific details are provided in the following description to provide a thorough understanding of examples. However, it will be understood by one of ordinary skill in the art that examples may be practiced without these specific details. For example, systems may be shown in block diagrams so as not to obscure the examples in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring examples.
In the following description, illustrative examples will be described with reference to acts and symbolic representations of operations (e.g., in the form of flow charts, flow diagrams, data flow diagrams, structure diagrams, block diagrams, etc.) that may be implemented as program services or functional processes include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types and may be implemented using hardware at network elements. Non-limiting examples of such hardware may include one or more Central Processing Units (CPUs), digital signal processors (DSPs), application-specific-integrated-circuits, field programmable gate arrays (FPGAs) computers or the like.
Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or can be learned by practice of the herein disclosed principles. The features and advantages of the disclosure can be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features of the disclosure will become more fully apparent from the following description and appended claims, or can be learned by the practice of the principles set forth herein.
A data center (DC) is an example of a cloud computing environment that can provide computing services to customers and users using shared resources. Cloud computing can generally include Internet-based computing in which computing resources are dynamically provisioned and allocated to client or user computers or other devices on-demand, from a collection of resources available via the network (e.g., “the cloud”). Cloud computing resources, for example, can include any type of resource, such as computing, storage, and network devices, virtual machines (VMs), containers, etc. For instance, resources may include service devices (firewalls, deep packet inspectors, traffic monitors, load balancers, etc.), compute/processing devices (servers, CPU's, memory, brute force processing capability), storage devices (e.g., network attached storages, storage area network devices), etc. In addition, such resources may be used to support virtual networks, virtual machines (VM), databases, containers that provide microservices, applications (Apps), etc.
Cloud computing resources may include a “private cloud,” a “public cloud,” and/or a “hybrid cloud.” A “hybrid cloud” can be a cloud infrastructure composed of two or more clouds that inter-operate or federate through technology. In essence, a hybrid cloud is an interaction between private and public clouds where a private cloud joins a public cloud and utilizes public cloud resources in a secure and scalable manner. Cloud computing resources can also be provisioned via virtual networks in an overlay network, such as a VXLAN.
Spine switches 104 can be L3 switches in the data center fabric 102. However, in some cases, the spine switches 104 can also, or otherwise, perform L2 functionalities. Further, the spine switches 104 can support various capabilities, such as 40 or 10 Gbps Ethernet speeds. To this end, the spine switches 104 can include one or more 40 Gigabit Ethernet ports. Each port can also be split to support other speeds. For example, a 40 Gigabit Ethernet port can be split into four 10 Gigabit Ethernet ports. Functionalities of spine switches 104 are not limited to that described above but may include any other known, or to be developed, functionality as known to those skilled in the art.
Spine switches 104 connect to leaf switches 106 in the data center fabric 102. Leaf switches 104 can include access ports (or non-fabric ports) and fabric ports. Fabric ports can provide uplinks to the spine switches 104, while access ports can provide connectivity for devices, hosts, endpoints, VMs, switches, servers running containers or external networks to the data center fabric 102.
Leaf switches 106 can reside at the edge of the data center fabric 102, and can thus represent the physical network edge. In some cases, the leaf switches 106 can be top-of-rack (“ToR”) switches configured according to a ToR architecture. In other cases, the leaf switches 104 can be aggregation switches in any particular topology, such as end-of-row (EoR) or middle-of-row (MoR) topologies. The leaf switches 106 can also represent aggregation switches, for example.
Leaf switches 104 can be responsible for routing and/or bridging the tenant packets and applying network policies. In some cases, a leaf switch can perform one or more additional functions, such as implementing a mapping cache, sending packets to the proxy function when there is a miss in the cache, encapsulate packets enforce ingress or egress policies, etc.
Network connectivity in data center fabric 102 can flow through leaf switches 106. Here, leaf switches 106 can provide servers, resources, endpoints, external networks, switches or VMs access to data center fabric 102, and can connect leaf switches 106 to each other. In some cases leaf switches 102 can connect Endpoint Groups (EPGs) to data center fabric 102 and/or any external networks. Each EPG can connect to data center fabric 102 via one of the leaf switches 106, for example.
DC 100 further includes one or more blade switches 108-1 and 108-2 (collectively referred to as blade switches 108 or switches 108). Blade switches 108 may be any known or to be developed blade switch such as various types of Fabric Interconnect (FI) blade switches designed and manufactured by Cisco Technology Inc., of San Jose, Calif. Alternatively, one or more of blade switches 108 may be any other known, or to be developed, blade switches that are available through any other switch/server and data center components manufacturer. Number of blade switches 108 is not limited to that shown in
Each of blade switches 108 can be connected to one or more of leaf switches 106.
DC 100 further includes one or more servers 110-1, 110-2 and 110-3 (collectively referred to as servers 110). Servers 110 can be any type of known or to be developed server including, but not limited to, known or to be developed blade servers. Servers 110 can be Uniform Computing System (UCS) blade servers designed and manufactured by Cisco Technology Inc., of San Jose, Calif. Alternatively, servers 110 can be any known, or to be developed, non-UCS blade servers available through any other switch/server and data center components manufacturer. The number of servers 110 is not limited to that shown in
In one example, one or more of the servers 110 may be a non-blade server that can be directly connected to one or more of leaf switches 106 without first being connected to an intermediary switch such as one of blade switches 108.
Each blade switch 108 can include a north-bound interface and south-bound interface that identify north-bound and south-bound neighbors of switch 108. In example of
Each one of blade servers 110 can be connected to one or more of blade switches 108 and/or, as described above, be directly connected to one or more of leaf switches 106.
Each of servers 110 may host one or more containers. Containers hosted by each of the servers 110 may be any know or to be developed container available and known to those skilled in the art. Furthermore, while reference is being made throughout this disclosure to containers and container workloads hosted by servers 110, servers 110 are not limited to hosting containers but can execute any other mechanism (e.g., a virtual machine) for providing virtual access to applications available thereon for consumers and customers. In one example, a given microservice (e.g., an application) can be provided via a single container or can span multiple containers that can be hosted on a single one of servers 110 or two or more of servers 110.
In one example, DC 100 includes a UCS manager 112 connected to each of servers 110 that is a blade server designed and manufactured by Cisco Technology Inc., of San Jose, Calif. (e.g., blade servers 110-1 and 110-2 shown in
In one example, DC 1.00 includes agent 114 deployed within each of servers 110 that is a non-UCS server designed and manufactured by manufacturers other than Cisco Technology, Inc. of San Jose, Calif. (e.g., blade server 110-3 shown in
In one example and as shown in
In another example, blade servers 110 of DC 100 are homogenous meaning that either all of blade servers 110 are designed and manufactured by Cisco Technology, Inc. of San Jose, Calif. (in which case, DC 100 does not include any agent 114) or all of blade servers are designed and manufactured by manufacturers other than Cisco Technology, Inc. of San Jose, Calif. (in which case, DC 100 does not include UCS manager 112).
DC 100 further includes an orchestration tool 116. Orchestration tool 116 may be any know or to be developed orchestration tool connected to servers 110 that among other functionalities, can be used to deploy containers on servers 110.
DC 100 also includes a data center network manager (DCNM) 118. DCNM 118 can also be referred to as controller 118. DCNM 118 can be a separate hardware (a processor and a memory) running computer-readable instructions that transform the processor into a special purpose processor for running network management functionalities, which include but is not limited to, providing an overview of DC 100 for operators (for purposes of provisioning, monitoring, and managing DC 100, understanding network usage, etc.).
Chipset 260 can also interface with one or more communication interfaces 290 that can have different physical interfaces. Such communication interfaces can include interfaces for wired and wireless local area networks, for broadband wireless networks, as well as personal area networks. Some applications of the methods for generating, displaying, and using the GUI disclosed herein can include receiving ordered datasets over the physical interface or be generated by the machine itself by processor 255 analyzing data stored in storage 270 or 275. Further, the machine can receive inputs from a user via user interface components 285 and execute appropriate functions, such as browsing functions by interpreting these inputs using processor 255.
It can be appreciated that Network device 250 can have more than one processor 210 or be part of a group or cluster of computing devices networked together to provide greater processing capability.
Alternatively, Network device 250 can be implemented on one of servers 110 shown in
At S300, UCS manager 112 (via a corresponding processor such as processor 255) receives a query from DCNM 118. The query can be communicated to UCS manager 112 by 118 through any known or to be developed wired and/or wireless communication means. In one example, the query is for link connectivity information. In one example, link connectivity information includes information about connectivity of UCS blade server(s) 110 and blade switch(es) 108 (one or more FI 108). This connectivity information about the UCS blade server(s) and each blade switch 108 may be referred to as south-bound neighboring information of a corresponding blade switch 108.
In one example, in addition to the south-bound neighboring information described above, link connectivity information also includes information about connectivity of each blade switch 108 to one or more of leaf switches 106. This connectivity information about each blade switch 108 and the one or more leaf switches 106 may be referred to as north-bound neighboring information of a corresponding blade switch 108.
In other words, link connectivity information includes information related to which blade server(s) 110 are connected to which blade switch 108 and which leaf switches 106 are connected to which blade switch 108.
At S310, UCS manager 112 determines link connectivity information. In one example, UCS manager 112 determines link connectivity information by determining LLDP and/or CDP neighbor information of each blade switch 108 obtained from inspecting LLDP/CDP frames. By inspecting LLDP/CDP frames between each blade switch 108 and one or more leaf switches 106, UCS manager 112 determines which leaf switches are connected to which blade switch 108.
Similarly, by inspecting LLDP/CDP frames between each blade server 110 and each blade switch 108, UCS manager 112 determines which blade server(s) 110 are connected to which blade switch 108.
In one example, UCS manager 112 performs the above process S310 for every blade switch 108 available and operating within DC 100.
At S320, UCS manager 112 returns (sends) the link connectivity information as determined at S310 to DCNM 118. UCS manager 112 can send the link connectivity information to DCNM 118 through any known or to be developed wired and/or wireless communication means.
At S400, DCNM 118 (via a corresponding processor such as processor 255) sends a query (e.g., a query for link connectivity information) to UCS manager 112 (network component), as described above with reference to
At S410, DCNM 118 receives link connectivity information determined and sent by UCS manager 112 (as described above with reference to S310 and S320 of
At S420, DCNM 118 correlates the received linked connectivity information with container workload information available to DCNM 118. Container workload information includes information indicating which containers are running on which each blade server 110. In one example, DCNM 118 receives notifications (which may or may not be periodic) from orchestration tool 116. Such notifications include information on changes to container(s) state (start, stop etc.) and the server(s) (e.g., server ID) on which each container is hosted.
At S430 and based on the correlation at S420, DCNM 118 determines which containers are connected to which one of leaf switches 106. This may be referred to as container to leaf switch connectivity information.
At S440 and based on the determined information at S430, DCNM 118 generates visual representation 120 of a topology of the DC 100, that also illustrates the container to leaf switch connectivity information between container workloads and their connectivity to each of leaf switches 106 thus providing a more complete and holistic view of DC 100 connectivity and operations.
As indicated above for each blade server on which containers are running, that is not manufactured by Cisco Technology Inc., of San Jose, Calif., an agent 114 (e.g., Cisco Container Telemetry Agent) is running thereon.
At S500, agent 114 periodically determines (collects) link connectivity information indicating blade server 110 to blade switch 108 connectivity. In one example, agent 114 determines this link connectivity information by inspecting (monitoring) LLDP/CDP frames between the corresponding blade server 110 and blade switch 108.
In one example, the periodicity according to which agent 114 collects link connectivity information is a configurable parameter determined by network/DC 100 operators, for example (e.g., every few seconds, minutes, hours, days, etc.).
At S510, agent 114 pushes (sends) the collected link connectivity information to a collector. In one example, the collector resides on DCNM 118. The collector makes the link connectivity information available to DCNM 118. In one example, instead of having the intermediate collector component present, agent 114 directly pushes the collected link connectivity information available to DCNM 118. Agent 114 can push the collected link connectivity information to the collector/DCNM 118 through any known or to be developed wired and/or wireless communication means.
In one example, instead of agents 114 periodically pushing link connectivity information to collector and ultimately to DCNM 118, DCNM 118 directly pulls (obtains by querying, for example) the link connectivity information from each of servers 110 thus eliminating the need for agents 114 and the collector residing on DCNM 118.
At S600, DCNM 118 (via a corresponding processor such as processor 255) receives collected link connectivity information from agent 114 (directly from agent 114 or from a collector associated with agent 14, as described above). DCNM 118 can receive the collected link connectivity information through any known or to be developed wired and/or wireless communication means.
At S610, DCNM 118 queries each of leaf switches 106 for corresponding leaf switches link connectivity information through any known or to be developed wired and/or wireless communication means (e.g., for LLDP/CDP neighboring information that indicate which blade switches (e.g., blade switch 108)).
At S620, using the collected link connectivity information received at S600, leaf switches link connectivity information received at S610 and information available to DCNM 118 that indicate which containers are running on which blade servers 110 (container workload information), DCNM 118 determines container to leaf switch connectivity information that indicate which containers are connected to which ones of leaf switches 106 (container to leaf switch connectivity information).
At S630 (similar to S440 described above), based on the determined container to leaf switch connectivity information at S620, DCNM 118 generates visual representation 120 of a topology of the DC 100, that also illustrates the container to leaf switch connectivity information between container workloads and their connectivity to each of leaf switches 106 thus providing a more complete and holistic view of DC 100 connectivity and operations.
As indicated above, DC 100 may be a hybrid network of blade servers and switches manufactured by Cisco Technology Inc., of San Jose, Calif. as well as one or more manufacturers other that Cisco Technology Inc. of San Jose, Calif. Accordingly, in such hybrid structure of DC 100, a combination of processes described with reference to
For clarity of explanation, in some instances the present technology may be presented as including individual functional blocks including functional blocks comprising devices, device components, steps or routines in a method embodied in software, or combinations of hardware and software.
In some examples the computer-readable storage devices, mediums, and memories can include a cable or wireless signal containing a bit stream and the like. However, when mentioned, non-transitory computer-readable storage media expressly exclude media such as energy, carrier signals, electromagnetic waves, and signals per se.
Methods according to the above-described examples can be implemented using computer-executable instructions that are stored or otherwise available from computer readable media. Such instructions can comprise, for example, instructions and data which cause or otherwise configure a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of function Portions of computer resources used can be accessible over a network. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, firmware, or source code. Examples of computer-readable media that may be used to store instructions, information used, and/or information created during methods according to described examples include magnetic or optical disks, flash memory, USB devices provided with non-volatile memory, networked storage devices, and so on.
Devices implementing methods according to these disclosures can comprise hardware, firmware and/or software, and can take any of a variety of form factors. Typical examples of such form factors include laptops, smart phones, small form factor personal computers, personal digital assistants, rackmount devices, standalone devices, and so on. Functionality described herein also can be embodied in peripherals or add-in cards. Such functionality can also be implemented on a circuit board among different chips or different processes executing in a single device, by way of further example.
The instructions, media for conveying such instructions, computing resources for executing them, and other structures for supporting such computing resources are means for providing the functions described in these disclosures.
Although a variety of examples and other information was used to explain aspects within the scope of the appended claims, no limitation of the claims should be implied based on particular features or arrangements in such examples, as one of ordinary skill would be able to use these examples to derive a wide variety of implementations. Further and although some subject matter may have been described in language specific to examples of structural features and/or method steps, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to these described features or acts. For example, such functionality can be distributed differently or performed in components other than those identified herein. Rather, the described features and steps are disclosed as examples of components of systems and methods within the scope of the appended claims. Moreover, claim language reciting “at least one of” a set indicates that one member of the set or multiple members of the set satisfy the claim.
This application is a continuation of U.S. Non-Provisional patent application Ser. No. 16/570,886, filed on Sep. 13, 2019, which is a continuation of U.S. Non-Provisional patent application Ser. No. 15/656,381, filed on Jul. 21, 2017, now U.S. Pat. No. 10,425,288, the full disclosure of each is hereby expressly incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5812773 | Norin | Sep 1998 | A |
5889896 | Meshinsky et al. | Mar 1999 | A |
6108782 | Fletcher et al. | Aug 2000 | A |
6178453 | Mattaway et al. | Jan 2001 | B1 |
6298153 | Oishi | Oct 2001 | B1 |
6343290 | Cossins et al. | Jan 2002 | B1 |
6643260 | Kloth et al. | Nov 2003 | B1 |
6683873 | Kwok et al. | Jan 2004 | B1 |
6721804 | Rubin et al. | Apr 2004 | B1 |
6733449 | Krishnamurthy et al. | May 2004 | B1 |
6735631 | Oehrke et al. | May 2004 | B1 |
6996615 | McGuire | Feb 2006 | B1 |
7054930 | Cheriton | May 2006 | B1 |
7058706 | Lyer et al. | Jun 2006 | B1 |
7062571 | Dale et al. | Jun 2006 | B1 |
7111177 | Chauvel et al. | Sep 2006 | B1 |
7212490 | Kao et al. | May 2007 | B1 |
7277948 | Igarashi et al. | Oct 2007 | B2 |
7313667 | Pullela et al. | Dec 2007 | B1 |
7379846 | Williams et al. | May 2008 | B1 |
7480672 | Hahn et al. | Jan 2009 | B2 |
7496043 | Leong et al. | Feb 2009 | B1 |
7536476 | Alleyne | May 2009 | B1 |
7567504 | Darling et al. | Jul 2009 | B2 |
7583665 | Duncan et al. | Sep 2009 | B1 |
7606147 | Luft et al. | Oct 2009 | B2 |
7644437 | Volpano | Jan 2010 | B2 |
7647594 | Togawa | Jan 2010 | B2 |
7773510 | Back et al. | Aug 2010 | B2 |
7808897 | Mehta et al. | Oct 2010 | B1 |
7881957 | Cohen et al. | Feb 2011 | B1 |
7917647 | Cooper et al. | Mar 2011 | B2 |
8010598 | Tanimoto | Aug 2011 | B2 |
8028071 | Mahalmgam et al. | Sep 2011 | B1 |
8041714 | Aymeloglu et al. | Oct 2011 | B2 |
8121117 | Amdahl et al. | Feb 2012 | B1 |
8160063 | Maltz et al. | Apr 2012 | B2 |
8171415 | Appleyard et al. | May 2012 | B2 |
8194534 | Pandey et al. | Jun 2012 | B2 |
8234377 | Cohn | Jul 2012 | B2 |
8244559 | Horvitz et al. | Aug 2012 | B2 |
8250215 | Stienhans et al. | Aug 2012 | B2 |
8280880 | Aymeloglu et al. | Oct 2012 | B1 |
8284664 | Aybay et al. | Oct 2012 | B1 |
8301746 | Head et al. | Oct 2012 | B2 |
8345692 | Smith | Jan 2013 | B2 |
8406141 | Couturier et al. | Mar 2013 | B1 |
8407413 | Yucel et al. | Mar 2013 | B1 |
8448171 | Donnellan et al. | May 2013 | B2 |
8477610 | Zuo et al. | Jul 2013 | B2 |
8495356 | Ashok et al. | Jul 2013 | B2 |
8495725 | Ahn | Jul 2013 | B2 |
8510469 | Portolani | Aug 2013 | B2 |
8514868 | Hill | Aug 2013 | B2 |
8532108 | Li et al. | Sep 2013 | B2 |
8533687 | Greifeneder et al. | Sep 2013 | B1 |
8547974 | Guruswamy et al. | Oct 2013 | B1 |
8560639 | Murphy et al. | Oct 2013 | B2 |
8560663 | Baucke et al. | Oct 2013 | B2 |
8589543 | Dutta et al. | Nov 2013 | B2 |
8590050 | Nagpal et al. | Nov 2013 | B2 |
8607225 | Stevens | Dec 2013 | B2 |
8611356 | Yu et al. | Dec 2013 | B2 |
8612625 | Andreis et al. | Dec 2013 | B2 |
8630291 | Shaffer et al. | Jan 2014 | B2 |
8639787 | Lagergren et al. | Jan 2014 | B2 |
8656024 | Krishnan et al. | Feb 2014 | B2 |
8660129 | Brendel et al. | Feb 2014 | B1 |
8719804 | Jain | May 2014 | B2 |
8775576 | Hebert et al. | Jul 2014 | B2 |
8797867 | Chen et al. | Aug 2014 | B1 |
8805951 | Faibish et al. | Aug 2014 | B1 |
8850002 | Dickinson et al. | Sep 2014 | B1 |
8850182 | Fritz et al. | Sep 2014 | B1 |
8856339 | Mestery et al. | Oct 2014 | B2 |
8909928 | Ahmad et al. | Dec 2014 | B2 |
8918510 | Gmach et al. | Dec 2014 | B2 |
8924720 | Raghuram et al. | Dec 2014 | B2 |
8930747 | Levijarvi et al. | Jan 2015 | B2 |
8938775 | Roth et al. | Jan 2015 | B1 |
8959526 | Kansal et al. | Feb 2015 | B2 |
8977754 | Curry, Jr. et al. | Mar 2015 | B2 |
9009697 | Breiter et al. | Apr 2015 | B2 |
9015324 | Jackson | Apr 2015 | B2 |
9043439 | Bicket et al. | May 2015 | B2 |
9049115 | Rajendran et al. | Jun 2015 | B2 |
9063789 | Beaty et al. | Jun 2015 | B2 |
9065727 | Liu et al. | Jun 2015 | B1 |
9075649 | Bushman et al. | Jul 2015 | B1 |
9128631 | Myrah et al. | Sep 2015 | B2 |
9130846 | Szabo et al. | Sep 2015 | B1 |
9164795 | Vincent | Oct 2015 | B1 |
9167050 | Durazzo et al. | Oct 2015 | B2 |
9201701 | Boldyrev et al. | Dec 2015 | B2 |
9201704 | Chang et al. | Dec 2015 | B2 |
9203784 | Chang et al. | Dec 2015 | B2 |
9223634 | Chang et al. | Dec 2015 | B2 |
9244776 | Koza et al. | Jan 2016 | B2 |
9251114 | Ancin et al. | Feb 2016 | B1 |
9264478 | Hon et al. | Feb 2016 | B2 |
9294408 | Dickinson et al. | Mar 2016 | B1 |
9313048 | Chang et al. | Apr 2016 | B2 |
9361192 | Smith et al. | Jun 2016 | B2 |
9379982 | Krishna et al. | Jun 2016 | B1 |
9380075 | He et al. | Jun 2016 | B2 |
9430262 | Felstaine et al. | Aug 2016 | B1 |
9432245 | Sorenson, III et al. | Aug 2016 | B1 |
9432294 | Sharma et al. | Aug 2016 | B1 |
9444744 | Sharma et al. | Sep 2016 | B1 |
9473365 | Melander et al. | Oct 2016 | B2 |
9503530 | Niedzielski | Nov 2016 | B1 |
9558078 | Farlee et al. | Jan 2017 | B2 |
9571570 | Mutnuru | Feb 2017 | B1 |
9613078 | Vermeulen et al. | Apr 2017 | B2 |
9628471 | Sundaram et al. | Apr 2017 | B1 |
9658876 | Chang et al. | May 2017 | B2 |
9692802 | Bicket et al. | Jun 2017 | B2 |
9755858 | Bagepalli et al. | Sep 2017 | B2 |
10171309 | Smith et al. | Jan 2019 | B1 |
10212041 | Rastogi | Feb 2019 | B1 |
10657019 | Chopra | May 2020 | B1 |
20010055303 | Horton et al. | Dec 2001 | A1 |
20020073337 | Ioele et al. | Jun 2002 | A1 |
20020143928 | Maltz et al. | Oct 2002 | A1 |
20020166117 | Abrams et al. | Nov 2002 | A1 |
20020174216 | Shorey et al. | Nov 2002 | A1 |
20030018591 | Komisky | Jan 2003 | A1 |
20030056001 | Mate et al. | Mar 2003 | A1 |
20030228585 | Inoko et al. | Dec 2003 | A1 |
20040004941 | Malan et al. | Jan 2004 | A1 |
20040034702 | He | Feb 2004 | A1 |
20040088542 | Daude et al. | May 2004 | A1 |
20040095237 | Chen et al. | May 2004 | A1 |
20040131059 | Ayyakad et al. | Jul 2004 | A1 |
20040197079 | Latvala et al. | Oct 2004 | A1 |
20040264481 | Darling et al. | Dec 2004 | A1 |
20050060418 | Sorokopud | Mar 2005 | A1 |
20050125424 | Herriott et al. | Jun 2005 | A1 |
20060062187 | Rune | Mar 2006 | A1 |
20060104286 | Cheriton | May 2006 | A1 |
20060126665 | Ward et al. | Jun 2006 | A1 |
20060146825 | Hofstaedter et al. | Jul 2006 | A1 |
20060155875 | Cheriton | Jul 2006 | A1 |
20060168338 | Bruegl et al. | Jul 2006 | A1 |
20060233106 | Achlioptas et al. | Oct 2006 | A1 |
20070174663 | Crawford et al. | Jul 2007 | A1 |
20070223487 | Kajekar et al. | Sep 2007 | A1 |
20070242830 | Conrado et al. | Oct 2007 | A1 |
20080005293 | Bhargava et al. | Jan 2008 | A1 |
20080080524 | Tsushima et al. | Apr 2008 | A1 |
20080084880 | Dharwadkar | Apr 2008 | A1 |
20080165778 | Ertemalp | Jul 2008 | A1 |
20080198752 | Fan et al. | Aug 2008 | A1 |
20080198858 | Townsley et al. | Aug 2008 | A1 |
20080201711 | Amir Husain | Aug 2008 | A1 |
20080235755 | Blaisdell et al. | Sep 2008 | A1 |
20090006527 | Gingell, Jr. et al. | Jan 2009 | A1 |
20090019367 | Cavagnari et al. | Jan 2009 | A1 |
20090031312 | Mausolf et al. | Jan 2009 | A1 |
20090083183 | Rao et al. | Mar 2009 | A1 |
20090138763 | Arnold | May 2009 | A1 |
20090177775 | Radia et al. | Jul 2009 | A1 |
20090178058 | Stillwell, III et al. | Jul 2009 | A1 |
20090182874 | Morford et al. | Jul 2009 | A1 |
20090265468 | Annambhotla et al. | Oct 2009 | A1 |
20090265753 | Anderson et al. | Oct 2009 | A1 |
20090293056 | Ferris | Nov 2009 | A1 |
20090300608 | Ferris et al. | Dec 2009 | A1 |
20090313562 | Appleyard et al. | Dec 2009 | A1 |
20090323706 | Germain et al. | Dec 2009 | A1 |
20090328031 | Pouyadou et al. | Dec 2009 | A1 |
20100036903 | Ahmad et al. | Feb 2010 | A1 |
20100042720 | Stienhans et al. | Feb 2010 | A1 |
20100061250 | Nugent | Mar 2010 | A1 |
20100110932 | Doran et al. | May 2010 | A1 |
20100115341 | Baker et al. | May 2010 | A1 |
20100131765 | Bromley et al. | May 2010 | A1 |
20100149966 | Achlioptas et al. | Jun 2010 | A1 |
20100191783 | Mason et al. | Jul 2010 | A1 |
20100192157 | Jackson et al. | Jul 2010 | A1 |
20100205601 | Abbas et al. | Aug 2010 | A1 |
20100211782 | Auradkar et al. | Aug 2010 | A1 |
20100293270 | Augenstein et al. | Nov 2010 | A1 |
20100318609 | Lahiri et al. | Dec 2010 | A1 |
20100325199 | Park et al. | Dec 2010 | A1 |
20100325441 | Laurie et al. | Dec 2010 | A1 |
20100333116 | Prahlad et al. | Dec 2010 | A1 |
20110016214 | Jackson | Jan 2011 | A1 |
20110035754 | Srinivasan | Feb 2011 | A1 |
20110055396 | Dehaan | Mar 2011 | A1 |
20110055398 | Dehaan et al. | Mar 2011 | A1 |
20110055470 | Portolani | Mar 2011 | A1 |
20110072489 | Parann-Nissany | Mar 2011 | A1 |
20110075667 | Li et al. | Mar 2011 | A1 |
20110110382 | Jabr et al. | May 2011 | A1 |
20110116443 | Yu et al. | May 2011 | A1 |
20110126099 | Anderson et al. | May 2011 | A1 |
20110138055 | Daly et al. | Jun 2011 | A1 |
20110145413 | Dawson et al. | Jun 2011 | A1 |
20110145657 | Bishop et al. | Jun 2011 | A1 |
20110173303 | Rider | Jul 2011 | A1 |
20110185063 | Head et al. | Jul 2011 | A1 |
20110185065 | Stanisic et al. | Jul 2011 | A1 |
20110206052 | Tan et al. | Aug 2011 | A1 |
20110213966 | Fu et al. | Sep 2011 | A1 |
20110219434 | Betz et al. | Sep 2011 | A1 |
20110231715 | Kunii et al. | Sep 2011 | A1 |
20110231899 | Pulier et al. | Sep 2011 | A1 |
20110239039 | Dieffenbach et al. | Sep 2011 | A1 |
20110252327 | Awasthi et al. | Oct 2011 | A1 |
20110261811 | Battestilli et al. | Oct 2011 | A1 |
20110261828 | Smith | Oct 2011 | A1 |
20110276675 | Singh et al. | Nov 2011 | A1 |
20110276951 | Jain | Nov 2011 | A1 |
20110283013 | Grosser et al. | Nov 2011 | A1 |
20110295998 | Ferris et al. | Dec 2011 | A1 |
20110305149 | Scott et al. | Dec 2011 | A1 |
20110307531 | Gaponenko et al. | Dec 2011 | A1 |
20110320870 | Kenigsberg et al. | Dec 2011 | A1 |
20120005724 | Lee | Jan 2012 | A1 |
20120036234 | Staats et al. | Feb 2012 | A1 |
20120054367 | Ramakrishnan et al. | Mar 2012 | A1 |
20120072318 | Akiyama et al. | Mar 2012 | A1 |
20120072578 | Alam | Mar 2012 | A1 |
20120072581 | Tung et al. | Mar 2012 | A1 |
20120072985 | Davne et al. | Mar 2012 | A1 |
20120072992 | Arasaratnam et al. | Mar 2012 | A1 |
20120084445 | Brock et al. | Apr 2012 | A1 |
20120084782 | Chou et al. | Apr 2012 | A1 |
20120096134 | Suit | Apr 2012 | A1 |
20120102193 | Rathore et al. | Apr 2012 | A1 |
20120102199 | Hopmann et al. | Apr 2012 | A1 |
20120131174 | Ferris et al. | May 2012 | A1 |
20120137215 | Kawara | May 2012 | A1 |
20120158967 | Sedayao et al. | Jun 2012 | A1 |
20120159097 | Jennas, II et al. | Jun 2012 | A1 |
20120167094 | Suit | Jun 2012 | A1 |
20120173710 | Rodriguez | Jul 2012 | A1 |
20120179909 | Sagi et al. | Jul 2012 | A1 |
20120180044 | Donnellan et al. | Jul 2012 | A1 |
20120182891 | Lee et al. | Jul 2012 | A1 |
20120185913 | Martinez et al. | Jul 2012 | A1 |
20120192016 | Gotesdyner et al. | Jul 2012 | A1 |
20120192075 | Ebtekar et al. | Jul 2012 | A1 |
20120201135 | Ding et al. | Aug 2012 | A1 |
20120214506 | Skaaksrud et al. | Aug 2012 | A1 |
20120222106 | Kuehl | Aug 2012 | A1 |
20120236716 | Anbazhagan et al. | Sep 2012 | A1 |
20120240113 | Hur | Sep 2012 | A1 |
20120265976 | Spiers et al. | Oct 2012 | A1 |
20120272025 | Park et al. | Oct 2012 | A1 |
20120281706 | Agarwal et al. | Nov 2012 | A1 |
20120281708 | Chauhan et al. | Nov 2012 | A1 |
20120290647 | Ellison et al. | Nov 2012 | A1 |
20120297238 | Watson et al. | Nov 2012 | A1 |
20120311106 | Morgan | Dec 2012 | A1 |
20120311568 | Jansen | Dec 2012 | A1 |
20120324092 | Brown et al. | Dec 2012 | A1 |
20120324114 | Dutta et al. | Dec 2012 | A1 |
20130003567 | Gallant et al. | Jan 2013 | A1 |
20130013248 | Brugler et al. | Jan 2013 | A1 |
20130036213 | Hasan et al. | Feb 2013 | A1 |
20130044636 | Koponen et al. | Feb 2013 | A1 |
20130066940 | Shao | Mar 2013 | A1 |
20130080509 | Wang | Mar 2013 | A1 |
20130080624 | Nagai et al. | Mar 2013 | A1 |
20130091557 | Gurrapu | Apr 2013 | A1 |
20130097601 | Podvialnik et al. | Apr 2013 | A1 |
20130104140 | Meng et al. | Apr 2013 | A1 |
20130111540 | Sabin | May 2013 | A1 |
20130117337 | Dunham | May 2013 | A1 |
20130124712 | Parker | May 2013 | A1 |
20130125124 | Kempf et al. | May 2013 | A1 |
20130138816 | Kuo et al. | May 2013 | A1 |
20130144978 | Jain et al. | Jun 2013 | A1 |
20130152076 | Patel | Jun 2013 | A1 |
20130152175 | Hromoko et al. | Jun 2013 | A1 |
20130159097 | Schory et al. | Jun 2013 | A1 |
20130159496 | Hamilton et al. | Jun 2013 | A1 |
20130160008 | Cawlfield et al. | Jun 2013 | A1 |
20130162753 | Hendrickson et al. | Jun 2013 | A1 |
20130169666 | Pacheco et al. | Jul 2013 | A1 |
20130179941 | McGloin et al. | Jul 2013 | A1 |
20130182712 | Aguayo et al. | Jul 2013 | A1 |
20130185433 | Zhu et al. | Jul 2013 | A1 |
20130191106 | Kephart et al. | Jul 2013 | A1 |
20130198374 | Zalmanovitch et al. | Aug 2013 | A1 |
20130201989 | Hu et al. | Aug 2013 | A1 |
20130204849 | Chacko | Aug 2013 | A1 |
20130232491 | Radhakrishnan et al. | Sep 2013 | A1 |
20130246588 | Borowicz et al. | Sep 2013 | A1 |
20130250770 | Zou et al. | Sep 2013 | A1 |
20130254415 | Fullen et al. | Sep 2013 | A1 |
20130262347 | Dodson | Oct 2013 | A1 |
20130283364 | Chang et al. | Oct 2013 | A1 |
20130297769 | Chang et al. | Nov 2013 | A1 |
20130318240 | Hebert et al. | Nov 2013 | A1 |
20130318546 | Kothuri et al. | Nov 2013 | A1 |
20130339949 | Spiers et al. | Dec 2013 | A1 |
20140006481 | Frey et al. | Jan 2014 | A1 |
20140006535 | Reddy | Jan 2014 | A1 |
20140006585 | Dunbar et al. | Jan 2014 | A1 |
20140040473 | Ho et al. | Feb 2014 | A1 |
20140040883 | Tompkins | Feb 2014 | A1 |
20140052877 | Mao | Feb 2014 | A1 |
20140056146 | Hu et al. | Feb 2014 | A1 |
20140059310 | Du et al. | Feb 2014 | A1 |
20140074850 | Noel et al. | Mar 2014 | A1 |
20140075048 | Yuksel et al. | Mar 2014 | A1 |
20140075108 | Dong et al. | Mar 2014 | A1 |
20140075357 | Flores et al. | Mar 2014 | A1 |
20140075501 | Srinivasan et al. | Mar 2014 | A1 |
20140089727 | Cherkasova et al. | Mar 2014 | A1 |
20140098762 | Ghai et al. | Apr 2014 | A1 |
20140108474 | David | Apr 2014 | A1 |
20140108985 | Scott et al. | Apr 2014 | A1 |
20140122560 | Ramey et al. | May 2014 | A1 |
20140136779 | Guha et al. | May 2014 | A1 |
20140140211 | Chandrasekaran et al. | May 2014 | A1 |
20140141720 | Princen et al. | May 2014 | A1 |
20140156557 | Zeng et al. | Jun 2014 | A1 |
20140164486 | Ravichandran et al. | Jun 2014 | A1 |
20140188825 | Muthukkaruppan et al. | Jul 2014 | A1 |
20140189095 | Lindberg et al. | Jul 2014 | A1 |
20140189125 | Amies et al. | Jul 2014 | A1 |
20140215471 | Cherkasova | Jul 2014 | A1 |
20140222953 | Karve et al. | Aug 2014 | A1 |
20140244851 | Lee | Aug 2014 | A1 |
20140245298 | Zhou et al. | Aug 2014 | A1 |
20140281173 | Im et al. | Sep 2014 | A1 |
20140282536 | Dave et al. | Sep 2014 | A1 |
20140282611 | Campbell et al. | Sep 2014 | A1 |
20140282889 | Ishaya et al. | Sep 2014 | A1 |
20140289200 | Kato | Sep 2014 | A1 |
20140295831 | Karra et al. | Oct 2014 | A1 |
20140297569 | Clark et al. | Oct 2014 | A1 |
20140297835 | Buys | Oct 2014 | A1 |
20140310391 | Sorensen, III et al. | Oct 2014 | A1 |
20140310417 | Sorensen, III et al. | Oct 2014 | A1 |
20140310418 | Sorensen, III et al. | Oct 2014 | A1 |
20140314078 | Jilani | Oct 2014 | A1 |
20140317261 | Shatzkamer et al. | Oct 2014 | A1 |
20140321278 | Cafarelli et al. | Oct 2014 | A1 |
20140330976 | van Bemmel | Nov 2014 | A1 |
20140330977 | van Bemmel | Nov 2014 | A1 |
20140334488 | Guichard et al. | Nov 2014 | A1 |
20140362682 | Guichard et al. | Dec 2014 | A1 |
20140365680 | van Bemmel | Dec 2014 | A1 |
20140366155 | Chang et al. | Dec 2014 | A1 |
20140369204 | Anand et al. | Dec 2014 | A1 |
20140372567 | Ganesh et al. | Dec 2014 | A1 |
20140379938 | Bosch et al. | Dec 2014 | A1 |
20150033086 | Sasturkar et al. | Jan 2015 | A1 |
20150043576 | Dixon et al. | Feb 2015 | A1 |
20150052247 | Threefoot et al. | Feb 2015 | A1 |
20150052517 | Raghu et al. | Feb 2015 | A1 |
20150058382 | St. Laurent et al. | Feb 2015 | A1 |
20150058459 | Amendjian et al. | Feb 2015 | A1 |
20150071285 | Kumar et al. | Mar 2015 | A1 |
20150074246 | Premji et al. | Mar 2015 | A1 |
20150085870 | Narasimha et al. | Mar 2015 | A1 |
20150089082 | Patwardhan et al. | Mar 2015 | A1 |
20150100471 | Curry, Jr. et al. | Apr 2015 | A1 |
20150103827 | Quinn et al. | Apr 2015 | A1 |
20150106802 | Ivanov et al. | Apr 2015 | A1 |
20150106805 | Melander et al. | Apr 2015 | A1 |
20150117199 | Chinnaiah Sankaran et al. | Apr 2015 | A1 |
20150117458 | Gurkan et al. | Apr 2015 | A1 |
20150120914 | Wada et al. | Apr 2015 | A1 |
20150124622 | Kovvali et al. | May 2015 | A1 |
20150138973 | Kumar et al. | May 2015 | A1 |
20150178133 | Phelan et al. | Jun 2015 | A1 |
20150189009 | van Bemmel | Jul 2015 | A1 |
20150215819 | Bosch et al. | Jul 2015 | A1 |
20150227405 | Jan et al. | Aug 2015 | A1 |
20150242204 | Hassine et al. | Aug 2015 | A1 |
20150249709 | Teng et al. | Sep 2015 | A1 |
20150263901 | Kumar et al. | Sep 2015 | A1 |
20150280980 | Bitar | Oct 2015 | A1 |
20150281067 | Wu | Oct 2015 | A1 |
20150281113 | Siciliano et al. | Oct 2015 | A1 |
20150309908 | Pearson et al. | Oct 2015 | A1 |
20150319063 | Zourzouvillys et al. | Nov 2015 | A1 |
20150326524 | Tankala et al. | Nov 2015 | A1 |
20150339210 | Kopp et al. | Nov 2015 | A1 |
20150358850 | La Roche, Jr. et al. | Dec 2015 | A1 |
20150365324 | Kumar et al. | Dec 2015 | A1 |
20150373108 | Fleming et al. | Dec 2015 | A1 |
20160011925 | Kulkarni et al. | Jan 2016 | A1 |
20160013990 | Kulkarni et al. | Jan 2016 | A1 |
20160026684 | Mukherjee et al. | Jan 2016 | A1 |
20160062786 | Meng et al. | Mar 2016 | A1 |
20160094389 | Jain et al. | Mar 2016 | A1 |
20160094398 | Choudhury et al. | Mar 2016 | A1 |
20160094453 | Jain et al. | Mar 2016 | A1 |
20160094454 | Jain et al. | Mar 2016 | A1 |
20160094455 | Jain et al. | Mar 2016 | A1 |
20160094456 | Jain et al. | Mar 2016 | A1 |
20160094480 | Kulkarni et al. | Mar 2016 | A1 |
20160094643 | Jain et al. | Mar 2016 | A1 |
20160099847 | Melander et al. | Apr 2016 | A1 |
20160099853 | Nedeltchev et al. | Apr 2016 | A1 |
20160099864 | Akiya et al. | Apr 2016 | A1 |
20160105393 | Thakkar et al. | Apr 2016 | A1 |
20160127184 | Bursell | May 2016 | A1 |
20160134557 | Steinder et al. | May 2016 | A1 |
20160156708 | Jalan et al. | Jun 2016 | A1 |
20160164780 | Timmons et al. | Jun 2016 | A1 |
20160164914 | Madhav et al. | Jun 2016 | A1 |
20160182378 | Basavaraja et al. | Jun 2016 | A1 |
20160188527 | Cherian et al. | Jun 2016 | A1 |
20160234071 | Nambiar et al. | Aug 2016 | A1 |
20160239399 | Babu et al. | Aug 2016 | A1 |
20160253078 | Ebtekar et al. | Sep 2016 | A1 |
20160254968 | Ebtekar et al. | Sep 2016 | A1 |
20160261564 | Foxhoven et al. | Sep 2016 | A1 |
20160277368 | Narayanaswamy et al. | Sep 2016 | A1 |
20160301603 | Park et al. | Oct 2016 | A1 |
20160330080 | Bhatia et al. | Nov 2016 | A1 |
20170005948 | Melander et al. | Jan 2017 | A1 |
20170024260 | Chandrasekaran et al. | Jan 2017 | A1 |
20170026294 | Basavaraja et al. | Jan 2017 | A1 |
20170026470 | Bhargava et al. | Jan 2017 | A1 |
20170041342 | Efremov et al. | Feb 2017 | A1 |
20170048100 | Delinocci | Feb 2017 | A1 |
20170054659 | Ergin et al. | Feb 2017 | A1 |
20170097841 | Chang et al. | Apr 2017 | A1 |
20170099188 | Chang et al. | Apr 2017 | A1 |
20170104755 | Arregoces et al. | Apr 2017 | A1 |
20170147297 | Krishnamurthy et al. | May 2017 | A1 |
20170149878 | Mutnuru | May 2017 | A1 |
20170163531 | Kumar et al. | Jun 2017 | A1 |
20170171158 | Hoy et al. | Jun 2017 | A1 |
20170264663 | Bicket et al. | Sep 2017 | A1 |
20170339070 | Chang et al. | Nov 2017 | A1 |
20170358111 | Madsen | Dec 2017 | A1 |
20170359223 | Hsu | Dec 2017 | A1 |
20180006894 | Power et al. | Jan 2018 | A1 |
20180034747 | Nataraja et al. | Feb 2018 | A1 |
20180062930 | Dhesikan et al. | Mar 2018 | A1 |
20180063025 | Nambiar et al. | Mar 2018 | A1 |
20180270125 | Jain | Sep 2018 | A1 |
20180359171 | Kommula et al. | Dec 2018 | A1 |
20190166013 | Shaikh | May 2019 | A1 |
Number | Date | Country |
---|---|---|
101719930 | Jun 2010 | CN |
101394360 | Jul 2011 | CN |
102164091 | Aug 2011 | CN |
104320342 | Jan 2015 | CN |
105740084 | Jul 2016 | CN |
2228719 | Sep 2010 | EP |
2439637 | Apr 2012 | EP |
2645253 | Nov 2014 | EP |
10-2015-0070676 | May 2015 | KR |
M394537 | Dec 2010 | TW |
WO 2009155574 | Dec 2009 | WO |
WO 2010030915 | Mar 2010 | WO |
WO 2013158707 | Oct 2013 | WO |
WO 2016146011 | Sep 2016 | WO |
Entry |
---|
Cisco Technology, Inc., “Cisco Expands Videoscape TV Platform Into the Cloud,” Jan. 6, 2014, Las Vegas, Nevada, Press Release, 3 pages. |
Citrix, “Citrix StoreFront 2.0” White Paper, Proof of Concept Implementation Guide, Citrix Systems, Inc., 2013, 48 pages. |
Citrix, “CloudBridge for Microsoft Azure Deployment Guide,” 30 pages. |
Citrix, “Deployment Practices and Guidelines for NetScaler 10.5 on Amazon Web Services,” White Paper, citrix.com, 2014, 14 pages. |
CSS Corp, “Enterprise Cloud Gateway (ECG)—Policy driven framework for managing multi-cloud environments,” original published on or about Feb. 11, 2012; 1 page; http://www.css-cloud.com/platform/enterprise-cloud-gateway.php. |
Fang K., “LISP MAC-EID-TO-RLOC Mapping (LISP based L2VPN),” Network Working Group, Internet Draft, CISCO Systems, Jan. 2012, 12 pages. |
Ford, Bryan, et al., Peer-to-Peer Communication Across Network Address Translators, In USENIX Annual Technical Conference, 2005, pp. 179-192. |
Gedymin, Adam, “Cloud Computing with an emphasis on Google App Engine,” Sep. 2011, 146 pages. |
Amedro, Brian, et al., “An Efficient Framework for Running Applications on Clusters, Grids and Cloud,” 2010, 17 pages. |
Author Unknown, “5 Benefits of a Storage Gateway in the Cloud,” Blog, Twinstrata, Inc., Jul. 25, 2012, XP055141645, 4 pages, https://web.archive.org/web/20120725092619/http://blog.twinstrata.com/2012/07/10//5-benefits-of-a-storage-gateway-in-the-cloud. |
Author Unknown, “Joint Cisco and VMWare Solution for Optimizing Virtual Desktop Delivery: Data Center 3.0: Solutions to Accelerate Data Center Virtualization,” Cisco Systems, Inc. and VMware, Inc., Sep. 2008, 10 pages. |
Author Unknown, “A Look at DeltaCloud: The Multi-Cloud API,” Feb. 17, 2012, 4 pages. |
Author Unknown, “About Deltacloud,” Apache Software Foundation, Aug. 18, 2013, 1 page. |
Author Unknown, “Architecture for Managing Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS0102, Jun. 18, 2010, 57 pages. |
Author Unknown, “Cloud Infrastructure Management Interface—Common Information Model (ClMI-CIM),” Document No. DSP0264, Version 1.0.0, Dec. 14, 2012, 21 pages. |
Author Unknown, “Cloud Infrastructure Management Interface (CIMI) Primer,” Document No. DSP2027, Version 1.0.1, Sep. 12, 2012, 30 pages. |
Author Unknown, “cloudControl Documentation,” Aug. 25, 2013, 14 pages. |
Author Unknown, “Interoperable Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS0101, Nov. 11, 2009, 21 pages. |
Author Unknown, “Microsoft Cloud Edge Gateway (MCE) Series Appliance,” Iron Networks, Inc., 2014, 4 pages. |
Author Unknown, “Open Data Center Alliance Usage: Virtual Machine (VM) Interoperability in a Hybrid Cloud Environment Rev. 1.2,” Open Data Center Alliance, Inc., 2013, 18 pages. |
Author Unknown, “Real-Time Performance Monitoring On Juniper Networks Devices, Tips and Tools for Assessing and Analyzing Network Efficiency,” Juniper Networks, Inc., May 2010, 35 pages. |
Author Unknown, “Use Cases and Interactions for Managing Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS00103, Jun. 16, 2010, 75 pages. |
Author Unknown, “Apache Ambari Meetup What's New,” Hortonworks Inc., Sep. 2013, 28 pages. |
Author Unknown, “Introduction,” Apache Ambari project, Apache Software Foundation, 2014, 1 page. |
Baker, F., “Requirements for IP Version 4 Routers,” Jun. 1995, 175 pages, Network Working Group, Cisco Systems. |
Beyer, Steffen, “Module “Data:Locations?!”,” YAPC::Europe, London, UKJCA, Sep. 22-24, 2000, XP002742700, 15 pages. |
Blanchet, M., “A Flexible Method for Managing the Assignment of Bits of an IPv6 Address Block,” Apr. 2003, 8 pages, Network Working Group, Viagnie. |
Borovick, Lucinda, et al., “Architecting the Network for the Cloud,” IDC White Paper, Jan. 2011, 8 pages. |
Bosch, Greg, “Virtualization,” last modified Apr. 2012 by B. Davison, 33 pages. |
Broadcasters Audience Research Board, “What's Next,” http://lwww.barb.co.uk/whats-next, accessed Jul. 22, 2015, 2 pages. |
Cisco Systems, Inc. “Best Practices in Deploying Cisco Nexus 1000V Series Switches on Cisco UCS B and C Series Cisco UCS Manager Servers,” Cisco White Paper, Apr. 2011, 36 pages, http://www.cisco.com/en/US/prod/collateral/switches/ps9441/ps9902/white_paper_c11-558242.pdf. |
Cisco Systems, Inc., “Cisco Unified Network Services: Overcome Obstacles to Cloud-Ready Deployments,” Cisco White Paper, Jan. 2011, 6 pages. |
Cisco Systems, Inc., “Cisco Intercloud Fabric: Hybrid Cloud with Choice, Consistency, Control and Compliance,” Dec. 10, 2014, 22 pages. |
Good, Nathan A., “Use Apache Deltacloud to administer multiple instances with a single API,” Dec. 17, 2012, 7 pages. |
Herry, William, “Keep It Simple, Stupid: OpenStack nova-scheduler and its algorithm”, May 12, 2012, IBM, 12 pages. |
Hewlett-Packard Company, “Virtual context management on network devices”, Research Disclosure, vol. 564, No. 60, Apr. 1, 2011, Mason Publications, Hampshire, GB, Apr. 1, 2011, 524. |
Juniper Networks, Inc., “Recreating Real Application Traffic in Junosphere Lab,” Solution Brief, Dec. 2011, 3 pages. |
Kenhui, “Musings On Cloud Computing and IT-as-a-Service: [Updated for Havana] Openstack Computer for VSphere Admins, Part 2: Nova-Scheduler and DRS”, Jun. 26, 2013, Cloud Architect Musings, 12 pages. |
Kolyshkin, Kirill, “Virtualization in Linux,” Sep. 1, 2006, XP055141648, 5 pages, https://web.archive.org/web/20070120205111/httD://download.openvz.org/doc/openvz-intro.pdf. |
Kumar, S., et al., “Infrastructure Service Forwarding For NSH,”Service Function Chaining Internet Draft, draft-kumar-sfc-nsh-forwarding-00, Dec. 5, 2015, 10 pages. |
Kunz, Thomas, et al., “OmniCloud—The Secure and Flexible Use of Cloud Storage Services,” 2014, 30 pages. |
Lerach, S.R.O., “Golem,” http://www.lerach.cz/en/products/golem, accessed Jul. 22, 2015, 2 pages. |
Linthicum, David, “VM Import could be a game changer for hybrid clouds”, IntoWorld, Dec. 23, 2010, 4 pages. |
Logan, Marcus, “Hybrid Cloud Application Architecture for Elastic Java-Based Web Applications,” F5 Deployment Guide Version 1.1, 2016, 65 pages. |
Lynch, Sean, “Monitoring cache with Claspin” Facebook Engineering, Sep. 19, 2012, 5 pages. |
Meireles, Fernando Miguel Dias, “Integrated Management of Cloud Computing Resources,” 2013-2014, 286 pages. |
Meraki, “meraki releases industry's first cloud-managed routers,” Jan. 13, 2011, 2 pages. |
Mu, Shuai, et al., “uLibCloud: Providing High Available and Uniform Accessing to Multiple Cloud Storages,” 2012 IEEE, 8 pages. |
Naik, Vijay K., et al., “Harmony: A Desktop Grid for Delivering Enterprise Computations,” Grid Computing, 2003, Fourth International Workshop on Proceedings, Nov. 17, 2003, pp. 1-11. |
Nair, Srijith K. et al., “Towards Secure Cloud Bursting, Brokerage and Aggregation,” 2012, 8 pages, www.flexiant.com. |
Nielsen, “SimMetry Audience Measurement—Technology,” http://www.nielsen-admosphere.eu/products-and-services/simmetry-audience-measurement-technology/ accessed Jul. 22, 2015, 6 pages. |
Nielsen, “Television,” http://www.nielsen.com/us/en/solutions/measurement/television.html, accessed Jul. 22, 2015, 4 pages. |
Open Stack, “Filter Scheduler,” updated Dec. 17, 2017, 5 pages, accessed on Dec. 18, 2017, https://docs.openstack.org/nova/latest/user/filter-scheduler.html. |
Quinn, P., et al., “Network Service Header,” Internet Engineering Task Force Draft, Jul. 3, 2014, 27 pages. |
Quinn, P., et al., “Service Function Chaining (SFC) Architecture,” Network Working Group, Internet Draft, draft-quinn-sfc-arch-03.txt, Jan. 22, 2014, 21 pages. |
Rabadan, J., et al., “Operational Aspects of Proxy-ARP/ND in EVPN Networks,” BESS Worksgroup Internet Draft, draft-snr-bess-evpn-proxy-arp-nd-02, Oct. 6, 2015, 22 pages. |
Saidi, Ali, et al., “Performance Validation of Network-Intensive Workloads on a Full-System Simulator,” Interaction between Operating System and Computer Architecture Workshop, (IOSCA 2005), Austin, Texas, Oct. 2005, 10 pages. |
Shunra, “Shunra for HP Software; Enabling Confidence in Application Performance Before Deployment,” 2010, 2 pages. |
Son, Jungmin, “Automatic decision system for efficient resource selection and allocation in inter-clouds,” Jun. 2013, 35 pages. |
Sun, Aobing, et al., “IaaS Public Cloud Computing Platform Scheduling Model and Optimization Analysis,” Int. J. Communications, Network and System Sciences, 2011,4, 803-811, 9 pages. |
Szymaniak, Michal, et al., “Latency-Driven Replica Placement”, vol. 47 No. 8, IPSJ Journal, Aug. 2006, 12 pages. |
Toews, Everett, “Introduction to Apache jclouds,” Apr. 7, 2014, 23 pages. |
Von Laszewski, Gregor, et al., “Design of a Dynamic Provisioning System for a Federated Cloud and Bare-metal Environment,” 2012, 8 pages. |
Wikipedia, “Filter (software)”, Wikipedia, Feb. 8, 2014, 2 pages, https://en.wikipedia.org/w/index.php?title=Filter %28software%29&oldid=594544359. |
Wikipedia; “Pipeline (Unix)”, Wikipedia, May 4, 2014, 4 pages, https://en.wikipedia.org/w/index.php?title=Pipeline2/028Unix%29&oldid=606980114. |
Ye, Xianglong, et al., “A Novel Blocks Placement Strategy for Hadoop,” 2012 IEEE/ACTS 11th International Conference on Computer and Information Science, 2012 IEEE, 5 pages. |
Number | Date | Country | |
---|---|---|---|
20220045912 A1 | Feb 2022 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 16570886 | Sep 2019 | US |
Child | 17510075 | US | |
Parent | 15656381 | Jul 2017 | US |
Child | 16570886 | US |