Embodiments relate to workload shaping and anomaly mitigation. More particularly, embodiments relate to techniques for dynamically workload management and anomaly mitigation in environments in which incoming requests can be inconsistent over time.
Subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed inventions.
Web applications in a multi tenant environment can share a multitude of resources. This approach works really well most of the time when the aggregate workload is within the planned/expected capacity envelope. However, at times, it is possible that a given actor (e.g., organization, user, service, tenant) or user may perform unusual workload/spikes that can affect other users consuming the same shared resources.
Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements.
In the following description, numerous specific details are set forth. However, embodiments of the invention may be practiced without these specific details. In other instances, well-known circuits, structures and techniques have not been shown in detail in order not to obscure the understanding of this description.
Embodiments described herein can be utilized to address workload shaping issues (including anomalies) by providing a workload regulator at the ‘edge’ of a system/environment that receives requests from external devices. The system (or environment) can be, for example, a group of servers providing services such as an on-demand services environment (e.g., multitenant database, software as a service (SaaS), messaging services, content management).
In one embodiment, the regulator can run on each of the application servers independently and may coordinate among themselves on as needed basis. Requests arriving on the system can be regulated using a variety and extensible set of actions. Requests can be accepted, rejected, re-routed, isolated, inspected, and/or delayed by a variety of strategies such as enqueueing and dispatching at a predetermined rate, enqueuing and dispatching maintaining a predetermined number of concurrent requests, enqueuing and dispatched based on resources availability and quality of service policies, etc.
In one embodiment, the regulator receives requests and determines, automatically in real-time, which requests to act on and what handling strategy to use. In one embodiment, this regulation behavior is determined by a set of one or more rules. In one embodiment, rules are essentially a filter and an action. The Filter determines what class of request attributes and features to select among all incoming request and the action determines what handling behavior is desired on the requests that satisfies the filter predicates.
In one embodiment, the filter can be any information derived from the web request, for example, the user, the originating customer institution, the target Universal Resource Indicator (URI) pattern, target resources such as databases, indexes, cache locality, etc. In one embodiment, actions are extensible and new actions can be created and added to the system. Example actions include: defer execution according to different strategies, reject the request, profile the request to better understand the use of certain resources, route to different cluster of servers or single servers based on a variety of strategies such as closeness to the required resources: data, caches, route to isolation server clusters, trace, custom scripts, etc.
In one embodiment, the mechanisms described herein behave seamlessly with respect to the downstream application. From the application perspective, regulated requests are no different from non-regulated requests. That makes the application development simpler.
In one embodiment, the mechanism uses real-time and historic metrics from a variety of resource classes to identify and classify usage patterns and infer adequate automatic actions. This allows for a proactive protection action allowing operations teams time to engage and identify the proper actions.
In one embodiment, the framework is extensible and new rules can be added to the system to support new behaviors. Also, rules can use other kinds of information to decide how to handle a given class of requests. For instance, different software license agreement (SLA) levels or contract rates (e.g., paying customer vs. free customers) may be handled differently to conform to a desirable serving policy.
In one embodiment, mechanisms described herein differ from traditional load balancing in that a load balancer focuses primarily at the network level and does not ‘understand’ the request at the application level, the dynamic and real-time resources being used by the system. In contrast, embodiments of the regulator can perform certain actions based on the specific organization, users, request performance traits, even the target data source or index, data source partition that the request needs.
Another difference is that load balancer does not dynamically seek to ‘smooth’ out spikes and resource constraints—it distributes it. The load balancer is also not adaptive to the system resources. The load balancer does not address the problem of anomaly detection—being resource induced or potentially malicious such as DOS attacks with the understanding of the resources topology and capacity. Embodiments of the regulators can function to grab spikes for a given organization/customer/user, dbnode, partition and put in a queue and pull them for execution at a controlled rate, identify requests that consume too much of resource class and route them to a dedicated cluster (or server) for isolation, investigation, block malicious fake logins, etc.
In one embodiment, operation of the regulator(s) can be based on the five rule types (block, throttle, trace, null, route), but the mechanism is extensible to other rule behaviors (profiling, notification, etc.).
Client device(s) 110 generate requests to the application servers, which are represented by request stream 120. The requests can be any type of requests directed to the application servers. In one embodiment, all requests from request stream 120 are received by one or more regulators 130. In one embodiment each application server can have a corresponding regulator. In other embodiments, application servers can share regulators or multiple regulators can be assigned to one or more application servers.
Regulator 130 provides the functionality discussed above. In one embodiment, regulator 130 includes costing on service metrics agent 140 that can operate to provide cost analysis for requests from request stream 120. Costing agent 140 can function to analyze resources required (and/or other costs) for servicing the request as part of analysis to determine how the corresponding request is to be handled.
In one embodiment, costing agent 140 can also include anomaly detector 144 that can operate to identify anomalous requests in request stream 120. Depending on the anomaly detected, regulator 130 can take different actions to respond to the anomaly. In one embodiment, costing agent 140 utilizes bounded Top-K heap 146 to perform costing analysis. Bounded Top-K heap 146 can provide, for example, lowest-cost or best-case allocations or other resource cost information related to incoming requests. In one embodiment, costing agent 140 provides results and/or analytical information to action enforcer 150 that initiates the action to be performed for a request.
In one embodiment, costing agent 140 analyzes historical data (e.g., number of requests over a period of time, amount of memory required to service concurrent requests, computational resources required for reports) to determine the resource costs for one or more requests. In an on-demand or multi-tenant environment, cost and/or historical information can be gathered and applied for individual customers/organizations/tenants/etc. Further information may be gathered with respect to the sources of the requests, for example, which users, geographic locations and/or other information. Thus, costing agent 140 aggregates various resource costs that can be used for decision making when scheduling/routing/processing incoming requests.
In one embodiment, bounded Top-K heap 146 is utilized to rank incoming requests base on cost metrics and/or other information. Bounded Top-K heap 146 can be utilized to identify outliers and anomalies for anomaly detector 144. These components can be utilized to determine, for example, excessive use of a resource by one or more client devices 110 or organizations.
In one embodiment, decision process and policy enforcer agent 145 applies policies to the requests. As discussed above, the policies may be based on one or more sets of rules. In one embodiment, policy enforcer agent 145 utilizes classification module 147 that provides classification rules and information, and quality of service (QoS) module 149 that provides QoS rules and information. Policy enforcer agent 145 can use different and/or additional information to enforce policies as described herein. In one embodiment, policy enforcer agent 145 provides results and/or analytical information to action enforcer 150 that initiates the action to be performed for a request.
In one embodiment, decision process and policy enforcer agent 145 determines the action to be taken for each request, for example, throttling, blocking, sending related requests to the same application server, or isolating/quarantining the requests. Other actions can also be supported. In one embodiment, classification module 147 can group requests that are similar. The characteristics that are utilized for classification can be, for example, request type, resource required, source of request, QoS category, etc. QoS module 149 provides QoS enforcement mechanisms for the incoming requests.
In one embodiment, action enforcer 150 enforces action utilizing at least information from costing agent 140 and policy enforcer agent 145. Action enforcer 150 can also provide analysis and enforcement functionality independent of or in addition to information received from costing agent 140 and or policy enforcer agent 145. In one embodiment, action enforcer 150 includes request inspector and metadata extraction module 155 that can determine information related to the request, for example, the identity of the user making the request, the company (if any) associated with the user, the customer organization/tenant (if any) associated with the user, resources required by the request and/or other information. Action enforcer 150 can apply the rules described above to requests and cause the appropriate action to be taken.
In one embodiment, action enforcer 150 includes rules engine 160 that provides one or more sets of rules that are utilized to regulate incoming requests. Various rule types can be supported. A few examples are discussed above and six specific examples are provided in
Inspection module 164 can provide rules and functionality for inspecting requests. For example, inspection module 164 can provide rules about what requests to inspect, what type of inspection/analysis to perform, what results to provide, etc. Routing module 166 can provide rules and functionality related to routing of requests. For example routing module 166 can provide rules for when requests are to be routed differently and/or how the requests are to be routed. For example, requests can be routed to a specific application server or cluster of application servers.
Block module 168 can provide rules and functionality related to blocking a request. For example, if a request comes from a source that is not allowed to access resources, the request can be blocked. In one embodiment, blocked requests are routed to isolation servers 180. Isolation module 170 can provide rules and functionality related to isolation of requests. In one embodiment, one or more suspected pernicious requests can be routed to isolation servers 180 temporarily or permanently. Custom module 172 can provide rules and functionality related to utilization of resources based on, for example, physical closeness.
After requests are analyzed and/or processed by regulator 130, the requests that are not dropped or isolated are sent to one or more application servers 190 that can function to service the request. The application servers can be organized as clusters or otherwise grouped. In one embodiment, one or more application servers 190 can provide metric feedback information 195 to regulator(s) 130. The feedback information can be any type of information related to the resources and/or functionality of application servers 190 that can be used for regulation purposes. For example, application servers 190 can provide feedback information indication memory and/or processor usage over time, the number of requests processes, etc.
Application servers 190 provide any type of server resources. For example, application servers can provide an on-demand services environment to service one or more of client devices 110. For example, application servers 190 can provide a multitenant environment (e.g., database, logistics, customer service) that provides services to multiple organizations/customers/tenants while keeping data for the respective organizations/customers/tenants secure and separate. Embodiments of multitenant environments are described in greater detail below.
With respect to a multitenant environment embodiment, web applications can share a multitude of resources. Under most conditions, the aggregate workload is within the planned/expected capacity envelope. However, at times, it is possible that a given organization or user may perform unusual workload/spikes that can affect other users consuming the same shared resources. The techniques described herein allow for management of the workload to respond to these spikes.
In one embodiment, the regulators run on each of the application servers of an on-demand or multi-tenant environment independently and the group of regulators can coordinate among themselves on as needed basis. Requests arriving on the system can be regulated using a variety and extensible set of actions. Requests can be accepted, rejected, re-routed, isolated, inspected, delayed by a variety of strategies such as enqueuing and dispatching at a predetermined rate, enqueuing and dispatching maintaining a predetermined number of concurrent requests, enqueuing and dispatched based on resources availability and quality of service policies, etc.
One or more requests are received with a regulator, 210. The requests are received from one or more client computing devices. The client computing devices can be, for example, laptop computers, tablets, smartphones, thin computing devices, desktop computers and/or wearable computing devices, etc. As discussed above, the regulator is conceptually on the edge of the receiving environment to intercept, or receive, the requests before the target server systems.
The regulator applies the rules, as discussed above, to determine if a regulation action is to be taken on a request, 220. In various embodiments, different rule sets can be applied to different requests based on, for example, source of the request, timing of the request, frequency of requests, etc. Global rule sets may also be applied. For example, in a multitenant environment, different tenants may have different rule sets applied.
In one embodiment, any information derived from the request can be utilized to determine the regulation action to be performed, for example, the user, the originating customer institution, the target Universal Resource Indicator (URI) pattern, target resources such as databases, indexes, cache locality, etc. In one embodiment, actions are extensible and new actions can be created and added to the system. Example actions include: defer execution according to different strategies, reject the request, profile the request to better understand the use of certain resources, route to different cluster of servers or single servers based on a variety of strategies such as closeness to the required resources: data, caches, route to isolation server clusters, trace, deep request inspection, custom scripts, etc.
The regulation action is performed, if necessary, 230. As discussed above, the regulation action can include, for example, requests can be accepted, rejected, re-routed, isolated, inspected, and/or delayed by a variety of strategies such as enqueuing and dispatching at a predetermined rate, enqueuing and dispatching maintaining a predetermined number of concurrent requests, enqueuing and dispatched based on resources availability and quality of service policies, etc.
Requests are serviced, 240. The request servicing can be performed by one or more application servers within the receiving environment. Requests that are not regulated are passed by the regulator(s) in the normal manner. Requests that are regulated (except for blocking and isolating) are processed by the application servers after regulation. The responses to the requests are sent back to the requesting client devices.
Environment 310 is an environment in which an on-demand database service exists. User system 312 may be any machine or system that is used by a user to access a database user system. For example, any of user systems 312 can be a handheld computing device, a mobile phone, a laptop computer, a work station, and/or a network of computing devices. As illustrated in herein
An on-demand database service, such as system 316, is a database system that is made available to outside users that do not need to necessarily be concerned with building and/or maintaining the database system, but instead may be available for their use when the users need the database system (e.g., on the demand of the users). Some on-demand database services may store information from one or more tenants stored into tables of a common database image to form a multi-tenant database system (MTS). Accordingly, “on-demand database service 316” and “system 316” will be used interchangeably herein. A database image may include one or more database objects. A relational database management system (RDMS) or the equivalent may execute storage and retrieval of information against the database object(s). Application platform 318 may be a framework that allows the applications of system 316 to run, such as the hardware and/or software, e.g., the operating system. In an embodiment, on-demand database service 316 may include an application platform 318 that enables creation, managing and executing one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 312, or third party application developers accessing the on-demand database service via user systems 312.
The users of user systems 312 may differ in their respective capacities, and the capacity of a particular user system 312 might be entirely determined by permissions (permission levels) for the current user. For example, where a salesperson is using a particular user system 312 to interact with system 316, that user system has the capacities allotted to that salesperson. However, while an administrator is using that user system to interact with system 316, that user system has the capacities allotted to that administrator. In systems with a hierarchical role model, users at one permission level may have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users will have different capabilities with regard to accessing and modifying application and database information, depending on a user's security or permission level.
Network 314 is any network or combination of networks of devices that communicate with one another. For example, network 314 can be any one or any combination of a LAN (local area network), WAN (wide area network), telephone network, wireless network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. As the most common type of computer network in current use is a TCP/IP (Transfer Control Protocol and Internet Protocol) network, such as the global internetwork of networks often referred to as the “Internet” with a capital “I,” that network will be used in many of the examples herein. However, it should be understood that the networks that one or more implementations might use are not so limited, although TCP/IP is a frequently implemented protocol.
User systems 312 might communicate with system 316 using TCP/IP and, at a higher network level, use other common Internet protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTP is used, user system 312 might include an HTTP client commonly referred to as a “browser” for sending and receiving HTTP messages to and from an HTTP server at system 316. Such an HTTP server might be implemented as the sole network interface between system 316 and network 314, but other techniques might be used as well or instead. In some implementations, the interface between system 316 and network 314 includes load sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a plurality of servers. At least as for the users that are accessing that server, each of the plurality of servers has access to the MTS' data; however, other alternative configurations may be used instead.
In one embodiment, system 316, shown in
One arrangement for elements of system 316 is shown in
Several elements in the system shown in
According to one embodiment, each user system 312 and all of its components are operator configurable using applications, such as a browser, including computer code run using a central processing unit such as an Intel Pentium® processor or the like. Similarly, system 316 (and additional instances of an MTS, where more than one is present) and all of their components might be operator configurable using application(s) including computer code to run using a central processing unit such as processor system 317, which may include an Intel Pentium® processor or the like, and/or multiple processor units. A computer program product embodiment includes a machine-readable storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the embodiments described herein. Computer code for operating and configuring system 316 to intercommunicate and to process webpages, applications and other data and media content as described herein are preferably downloaded and stored on a hard disk, but the entire program code, or portions thereof, may also be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disk (DVD), compact disk (CD), microdrive, and magneto-optical disks, and magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, e.g., over the Internet, or from another server, as is well known, or transmitted over any other conventional network connection as is well known (e.g., extranet, VPN, LAN, etc.) using any communication medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for implementing embodiments can be implemented in any programming language that can be executed on a client system and/or server or server system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).
According to one embodiment, each system 316 is configured to provide webpages, forms, applications, data and media content to user (client) systems 312 to support the access by user systems 312 as tenants of system 316. As such, system 316 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (e.g., in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (e.g., one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically and/or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to include a computer system, including processing hardware and process space(s), and an associated storage system and database application (e.g., OODBMS or RDBMS) as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database object described herein can be implemented as single databases, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and might include a distributed database or storage network and associated processing intelligence.
User system 312, network 314, system 316, tenant data storage 322, and system data storage 324 were discussed above in
Application platform 318 includes an application setup mechanism 438 that supports application developers' creation and management of applications, which may be saved as metadata into tenant data storage 322 by save routines 436 for execution by subscribers as one or more tenant process spaces 404 managed by tenant management process space 410 for example. Invocations to such applications may be coded using PL/SOQL 434 that provides a programming language style interface extension to API 432. A detailed description of some PL/SOQL language embodiments is discussed in commonly owned U.S. Pat. No. 7,730,478 entitled, “Method and System for Allowing Access to Developed Applicants via a Multi-Tenant Database On-Demand Database Service” issued Jun. 1, 2010 to Craig Weissman, which is incorporated in its entirety herein for all purposes. Invocations to applications may be detected by one or more system processes, which manage retrieving application metadata 416 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.
Each application server 400 may be communicably coupled to database systems, e.g., having access to system data 325 and tenant data 323, via a different network connection. For example, one application server 4001 might be coupled via the network 314 (e.g., the Internet), another application server 400N-1 might be coupled via a direct network link, and another application server 400N might be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are typical protocols for communicating between application servers 400 and the database system. However, it will be apparent to one skilled in the art that other transport protocols may be used to optimize the system depending on the network interconnect used.
In certain embodiments, each application server 400 is configured to handle requests for any user associated with any organization that is a tenant. Because it is desirable to be able to add and remove application servers from the server pool at any time for any reason, there is preferably no server affinity for a user and/or organization to a specific application server 400. In one embodiment, therefore, an interface system implementing a load balancing function (e.g., an F5 Big-IP load balancer) is communicably coupled between the application servers 400 and the user systems 312 to distribute requests to the application servers 400. In one embodiment, the load balancer uses a least connections algorithm to route user requests to the application servers 400. Other examples of load balancing algorithms, such as round robin and observed response time, also can be used. For example, in certain embodiments, three consecutive requests from the same user could hit three different application servers 400, and three requests from different users could hit the same application server 400. In this manner, system 316 is multi-tenant, wherein system 316 handles storage of, and access to, different objects, data and applications across disparate users and organizations.
As an example of storage, one tenant might be a company that employs a sales force where each salesperson uses system 316 to manage their sales process. Thus, a user might maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (e.g., in tenant data storage 322). In an example of a MTS arrangement, since all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system having nothing more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, if a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates as to that customer while waiting for the customer to arrive in the lobby.
While each user's data might be separate from other users' data regardless of the employers of each user, some data might be organization-wide data shared or accessible by a plurality of users or all of the users for a given organization that is a tenant. Thus, there might be some data structures managed by system 316 that are allocated at the tenant level while other data structures might be managed at the user level. Because an MTS might support multiple tenants including possible competitors, the MTS should have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that may be implemented in the MTS. In addition to user-specific data and tenant specific data, system 316 might also maintain system level data usable by multiple tenants or other data. Such system level data might include industry reports, news, postings, and the like that are sharable among tenants.
In certain embodiments, user systems 312 (which may be client systems) communicate with application servers 400 to request and update system-level and tenant-level data from system 316 that may require sending one or more queries to tenant data storage 322 and/or system data storage 324. System 316 (e.g., an application server 400 in system 316) automatically generates one or more SQL statements (e.g., one or more SQL queries) that are designed to access the desired information. System data storage 324 may generate query plans to access the requested data from the database.
Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined categories. A “table” is one representation of a data object, and may be used herein to simplify the conceptual description of objects and custom objects. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or record of a table contains an instance of data for each category defined by the fields. For example, a CRM database may include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table might describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some multi-tenant database systems, standard entity tables might be provided for use by all tenants. For CRM database applications, such standard entities might include tables for Account, Contact, Lead, and Opportunity data, each containing pre-defined fields. It should be understood that the word “entity” may also be used interchangeably herein with “object” and “table”.
In some multi-tenant database systems, tenants may be allowed to create and store custom objects, or they may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. U.S. patent application Ser. No. 10/817,161, filed Apr. 2, 2004, entitled “Custom Entities and Fields in a Multi-Tenant Database System”, and which is hereby incorporated herein by reference, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In certain embodiments, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.
Any of the above embodiments may be used alone or together with one another in any combination. Embodiments encompassed within this specification may also include embodiments that are only partially mentioned or alluded to or are not mentioned or alluded to at all in this brief summary or in the abstract. Although various embodiments may have been motivated by various deficiencies with the prior art, which may be discussed or alluded to in one or more places in the specification, the embodiments do not necessarily address any of these deficiencies. In other words, different embodiments may address different deficiencies that may be discussed in the specification. Some embodiments may only partially address some deficiencies or just one deficiency that may be discussed in the specification, and some embodiments may not address any of these deficiencies.
Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
While the invention has been described in terms of several embodiments, those skilled in the art will recognize that the invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. The description is thus to be regarded as illustrative instead of limiting.
This application claims priority to Provisional U.S. patent application Ser. No. 61/888,788, filed on Oct. 9, 2013, entitled “Extensible Mechanism for Workload Shaping,” by Fabio Valbuena, which is incorporated herein by reference in its entirety and for all purposes.
Number | Name | Date | Kind |
---|---|---|---|
5577188 | Zhu | Nov 1996 | A |
5608872 | Schwartz et al. | Mar 1997 | A |
5649104 | Carleton et al. | Jul 1997 | A |
5715450 | Ambrose et al. | Feb 1998 | A |
5761419 | Schwartz et al. | Jun 1998 | A |
5819038 | Carleton et al. | Oct 1998 | A |
5821937 | Tonelli et al. | Oct 1998 | A |
5831610 | Tonelli et al. | Nov 1998 | A |
5873096 | Lim et al. | Feb 1999 | A |
5918159 | Fomukong et al. | Jun 1999 | A |
5963953 | Cram et al. | Oct 1999 | A |
6092083 | Brodersen et al. | Jul 2000 | A |
6169534 | Raffel et al. | Jan 2001 | B1 |
6178425 | Brodersen et al. | Jan 2001 | B1 |
6189011 | Lim et al. | Feb 2001 | B1 |
6216135 | Brodersen et al. | Apr 2001 | B1 |
6233617 | Rothwein et al. | May 2001 | B1 |
6266669 | Brodersen et al. | Jul 2001 | B1 |
6295530 | Ritchie et al. | Sep 2001 | B1 |
6324568 | Diec | Nov 2001 | B1 |
6324693 | Brodersen et al. | Nov 2001 | B1 |
6336137 | Lee et al. | Jan 2002 | B1 |
D454139 | Feldcamp | Mar 2002 | S |
6367077 | Brodersen et al. | Apr 2002 | B1 |
6393605 | Loomans | May 2002 | B1 |
6405220 | Brodersen et al. | Jun 2002 | B1 |
6434550 | Warner et al. | Aug 2002 | B1 |
6446089 | Brodersen et al. | Sep 2002 | B1 |
6535909 | Rust | Mar 2003 | B1 |
6549908 | Loomans | Apr 2003 | B1 |
6553563 | Ambrose et al. | Apr 2003 | B2 |
6560461 | Fomukong et al. | May 2003 | B1 |
6574635 | Stauber et al. | Jun 2003 | B2 |
6577726 | Huang et al. | Jun 2003 | B1 |
6601087 | Zhu et al. | Jul 2003 | B1 |
6604117 | Lim et al. | Aug 2003 | B2 |
6604128 | Diec | Aug 2003 | B2 |
6609150 | Lee et al. | Aug 2003 | B2 |
6621834 | Scherpbier et al. | Sep 2003 | B1 |
6654032 | Zhu et al. | Nov 2003 | B1 |
6665648 | Brodersen et al. | Dec 2003 | B2 |
6665655 | Warner et al. | Dec 2003 | B1 |
6684438 | Brodersen et al. | Feb 2004 | B2 |
6711565 | Subramaniam et al. | Mar 2004 | B1 |
6724399 | Katchour et al. | Apr 2004 | B1 |
6728702 | Subramaniam et al. | Apr 2004 | B1 |
6728960 | Loomans | Apr 2004 | B1 |
6732095 | Warshaysky et al. | May 2004 | B1 |
6732100 | Brodersen et al. | May 2004 | B1 |
6732111 | Brodersen et al. | May 2004 | B2 |
6754681 | Brodersen et al. | Jun 2004 | B2 |
6763351 | Subramaniam et al. | Jul 2004 | B1 |
6763501 | Zhu et al. | Jul 2004 | B1 |
6768904 | Kim | Jul 2004 | B2 |
6782383 | Subramaniam et al. | Aug 2004 | B2 |
6804330 | Jones et al. | Oct 2004 | B1 |
6826565 | Ritchie et al. | Nov 2004 | B2 |
6826582 | Chatterjee et al. | Nov 2004 | B1 |
6826745 | Coker et al. | Nov 2004 | B2 |
6829655 | Huang et al. | Dec 2004 | B1 |
6842748 | Warner et al. | Jan 2005 | B1 |
6850895 | Brodersen et al. | Feb 2005 | B2 |
6850949 | Warner et al. | Feb 2005 | B2 |
7206805 | McLaughlin, Jr. | Apr 2007 | B1 |
7340411 | Cook | Mar 2008 | B2 |
7620655 | Larsson et al. | Nov 2009 | B2 |
9244958 | MacCanti | Jan 2016 | B1 |
9292348 | Adams | Mar 2016 | B2 |
20010044791 | Richter et al. | Nov 2001 | A1 |
20020022986 | Coker et al. | Feb 2002 | A1 |
20020029161 | Brodersen et al. | Mar 2002 | A1 |
20020029376 | Ambrose et al. | Mar 2002 | A1 |
20020035577 | Brodersen et al. | Mar 2002 | A1 |
20020042264 | Kim | Apr 2002 | A1 |
20020042843 | Diec | Apr 2002 | A1 |
20020072951 | Lee et al. | Jun 2002 | A1 |
20020082892 | Raffel et al. | Jun 2002 | A1 |
20020129352 | Brodersen et al. | Sep 2002 | A1 |
20020140731 | Subramaniam et al. | Oct 2002 | A1 |
20020143997 | Huang et al. | Oct 2002 | A1 |
20020152102 | Brodersen et al. | Oct 2002 | A1 |
20020161734 | Stauber et al. | Oct 2002 | A1 |
20020162090 | Parnell et al. | Oct 2002 | A1 |
20020165742 | Robins | Nov 2002 | A1 |
20030004971 | Gong et al. | Jan 2003 | A1 |
20030018705 | Chen et al. | Jan 2003 | A1 |
20030018830 | Chen et al. | Jan 2003 | A1 |
20030066031 | Laane | Apr 2003 | A1 |
20030066032 | Ramachadran et al. | Apr 2003 | A1 |
20030069936 | Warner et al. | Apr 2003 | A1 |
20030070000 | Coker et al. | Apr 2003 | A1 |
20030070004 | Mukundan et al. | Apr 2003 | A1 |
20030070005 | Mukundan et al. | Apr 2003 | A1 |
20030074418 | Coker | Apr 2003 | A1 |
20030088545 | Subramaniam et al. | May 2003 | A1 |
20030120675 | Stauber et al. | Jun 2003 | A1 |
20030151633 | George et al. | Aug 2003 | A1 |
20030159136 | Huang et al. | Aug 2003 | A1 |
20030187921 | Diec | Oct 2003 | A1 |
20030189600 | Gune et al. | Oct 2003 | A1 |
20030191743 | Brodersen et al. | Oct 2003 | A1 |
20030204427 | Gune et al. | Oct 2003 | A1 |
20030206192 | Chen et al. | Nov 2003 | A1 |
20030225730 | Warner et al. | Dec 2003 | A1 |
20040001092 | Rothwein et al. | Jan 2004 | A1 |
20040010489 | Rio | Jan 2004 | A1 |
20040015981 | Coker et al. | Jan 2004 | A1 |
20040027388 | Berg et al. | Feb 2004 | A1 |
20040128001 | Levin et al. | Jul 2004 | A1 |
20040186860 | Lee et al. | Sep 2004 | A1 |
20040193510 | Catahan, Jr. et al. | Sep 2004 | A1 |
20040199489 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199536 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199543 | Braud et al. | Oct 2004 | A1 |
20040236757 | Caccavale | Nov 2004 | A1 |
20040249854 | Barnes-Leon et al. | Dec 2004 | A1 |
20040260534 | Pak et al. | Dec 2004 | A1 |
20040260659 | Chan et al. | Dec 2004 | A1 |
20040268299 | Lei et al. | Dec 2004 | A1 |
20050050555 | Exley et al. | Mar 2005 | A1 |
20050091098 | Brodersen et al. | Apr 2005 | A1 |
20080276238 | Levanoni | Nov 2008 | A1 |
20120054765 | Lee | Mar 2012 | A1 |
20140325524 | Zangaro | Oct 2014 | A1 |
Number | Date | Country | |
---|---|---|---|
20150100698 A1 | Apr 2015 | US |
Number | Date | Country | |
---|---|---|---|
61888788 | Oct 2013 | US |