The present invention relates to the field of cloud computing, and, in particular embodiments, to a system and method for controlling management operations and shared memory space for cloud cache service.
Cloud computing is a form of network-based computing (e.g., Internet-based computing) that enables access to shared pools of configurable computing resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet. Cloud computing is another paradigm shift that follows the shift from mainframe based computing to client-server based computing that is implemented as services. Cloud computing service providers generally deliver three main types of services (referred to hereinafter as cloud computing services), infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS), by creating virtual machines on demand for use by customers. IaaS provides a computing infrastructure that can be rented and used by customers. The computing infrastructure comprises physical computing resources (e.g., processors, memory, storage, servers, networking components, etc.) that are virtualized and shared among customers. PaaS provides a platform that allows customers to develop, run, and manage software applications without having to build and maintain the computing infrastructure. SaaS provides software applications running on the computing infrastructure on demand over the Internet on a subscription basis. One type of PaaS provided by cloud service providers is a cloud caching service to provide in-memory data storage for software applications running on the computing infrastructure to shorten data access times, reduce latency, and improve input/output (IO) operations. Improvements to the performance of cloud caching services are desirable.
Technical advantages are generally achieved by embodiments of this disclosure which describe a systems and method for controlling management operations and shared memory space for cloud cache service.
In accordance with embodiments, methods for controlling cloud cache management operations and shared memory space are disclosed. A cloud cache management controller may receive multiple sets of service attributes. Each set of the multiple sets of service attributes may be related to a cloud cache service instance. The cloud cache management controller may receive a first cloud cache management request. The cloud cache management request may comprise a cloud cache management operation. The cloud cache management controller may retrieve a set of service attributes from the multiple sets of service attributes based on an evaluation of the cloud cache management operation. The cloud cache management controller may send the first cloud cache management request to a corresponding CCSI based on a priority value for the first cloud cache management request calculated based on the retrieved set of service attributes.
Devices, as well as computer program products, for performing the methods are also provided.
For a more complete understanding of the present invention, and the advantages thereof, reference is now made to the following description taken in conjunction with the accompanying drawings, in which:
Corresponding numerals and symbols in the different figures generally refer to corresponding parts unless otherwise indicated. The figures are drawn to clearly illustrate the relevant aspects of the embodiments and are not necessarily drawn to scale.
The making and using of embodiments of this disclosure are discussed in detail below. It should be appreciated, however, that the present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific ways to make and use the invention, and do not limit the scope of the invention. These and other inventive aspects are described in greater detail below.
The operating of the current example embodiments and the structure thereof are discussed in detail below. It should be appreciated, however, that the present disclosure provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific structures of the embodiments and ways to operate the embodiments disclosed herein, and do not limit the scope of the disclosure.
Cloud caching service is a PasS middleware service that is commonly used to enhance the performance for applications running on virtual machines instantiated in the cloud. Cloud caching service offers in-memory data storage, normally on cloud cache service nodes, for applications to access data at high speed. Cloud caching service must be able to respond to large volumes of concurrent requests for in-memory data storage while maintaining low latency and high throughput. Accordingly, cloud caching service has a high demand to enhance its performance and resource utilization. A system that provides a cloud caching service (referred to hereinafter as a cloud caching service system) often processes and responds to cloud cache management operations and cloud cache user operations. Cloud cache management operations generally relate to maintenance of the cloud caching service, such as backup, restore, and migration of data in a cloud cache. Cloud cache user operations relate access of cached data used by cloud applications.
The virtualization layer 110 supports a flexible and efficient multi-tenancy run-time and hosting environment for applications 112 by providing Infrastructure as a Service (IaaS) facilities. The virtualization layer 110 includes a virtualization manager or hypervisor (not shown) that may provide a security and resource “sandbox” for each application 112 being hosted by the application platform 104. Each “sandbox” may be implemented as a Virtual Machine (VM) 118 (e.g., virtual computing device) that may include an appropriate operating system and controlled access to a set of virtual computing resources, such as virtualized processing resources, storage resources (e.g. virtual storage 120), and networking resources.
The virtualization of the physical hardware resources 108 by the virtualization layer 110 is considered to be foundational technology for the cloud 100. Virtualization of is a technology that allows for the creation of virtual computing resource pools of computing resources (e.g., processing, storage, and networking resources) connected to each by connectivity resources. Virtualization may take the form of instantiating VMs 118 that, to another entity on a network and to software executed on the VM 118, is no different than a physical computing device. A VM 118 has its own set of computing resources (e.g., processing, storage, and connectivity resources), upon which an operating system can be executed. The VM 118 can have a virtual network interface that can be assigned a network address. Between the underlying resources and the VM 118, there is typically a hypervisor (not shown) that manages the resource isolation and network interactions. One of the purposes of a VM 118 is to provide isolation from other processes running on the cloud 100. When initially developed, a VM 118 was a mechanism to allow different processes to operate without concern that a single errant process would be able to cause a complete system crash. Instead, an errant process would be contained to its own VM 118. This isolation allows for each VM 118 to have its own set of network interfaces. Typically, a single underlying computing resource can support a plurality of virtualized entities.
It will be appreciated by those skilled in the art that a more recent development has been the use of containers in place of VMs 118. As mentioned above, each VM 118 typically includes its own operating system which typically increases redundant computing, storage, and connectivity resource usage. Containers allow a single OS kernel to support a number of isolated applications. In place of a hypervisor that allows each VM 118 to run its own OS, a single OS hosts containers that are responsible for enforcing the resource isolation that would otherwise be provided by the VM 118.
The application platform 104 provides the capabilities for hosting applications 112 and includes application platform services 122. The application platform services 122 provide a set of middleware application services and infrastructure services to the applications 112 hosted on the application platform 104. In the embodiment depicted in
A cloud application 158, or cloud app, is a software application that that is deployed and executed on a virtual machine of the cloud 100 or an instance of an application 112 provided by the SaaS and hosted by application platform 104 of the cloud 100. Cloud applications 158 are a blend of standard web or mobile applications and conventional desktop applications. A cloud application 158 is a software program where cloud-based/server-side components and local/client-side components of the application work together. Examples of cloud applications 158 may include, but are not limited to, web based word processing programs and web based spreadsheet applications. The model of cloud applications relies on remote servers resident in a data center for the processing logic and data that is accessed through a local client web browser with a continual reliable network connection. Cloud applications 158 do not require large amounts of storage in the user's client device. If the client device associated with the user 152 has a fast Internet connection, an efficient cloud application can offer the interaction of a local/client-side application together with the portability of a web application. For example, a client device associated with user 152 may provide a web browser and an Internet connection that can easily allow user 152 access and use the cloud applications 158, through a local graphical user interface (not shown in
When the client device associated with user 152 accesses and uses one of the cloud applications 158, the application platform 104 may instantiate a corresponding instance of a cloud application (referred to hereinafter as a cloud application instance 160) for that cloud application. For example, if a user 152 uses a web browser or mobile application of a client device to open a word document, a cloud application instance 160 of a cloud application (e.g., a cloud-based word processing application) provided by the SaaS is instantiated in the cloud 100 to process the word document. Cloud application instance 160 may fetch or modify data associated with the word document, which is permanently stored in database 162 provided by the database service 126. Database 162 may be instantiated on one or more physical hardware resources 108 of the cloud 100.
Fetching and/or modifying data in database 162 requires access to the physical hardware resources 108 (e.g., physical storage resources) used by database 162. Accessing physical hardware resources 108 (e.g., physical storage resources) can be slow. To improve the response time, the cloud 100 generally includes a cloud cache service system 156 for providing a cloud caching service 124. A cache is a high-speed data storage which stores a subset of data, typically transient in nature, so that future requests for that data can be retrieved from the cache faster than it is possible by retrieving the data from the physical storage resources of the physical hardware resources 108. In one example, cloud cache service system 156 may provide managed, in-memory data store and caching service that enables hosted and managed cloud applications to retrieve and modify data faster (e.g., in less time) than retrieving and modifying data from database 162.
Data in cache service system 156 is generally stored in fast access physical hardware resources, such as RAM (random-access memory), which is faster but has smaller storage capacity than the physical storage resources the database 162 is instantiated on. Some non-limiting examples of cache service system 156 may include Amazon ElastiCache, Microsoft Azure Redis Cache, Google Memcache, IBM Compose for Redis, and Alibaba ApsaraDB for Redis. Data in cache service system 156 may be used in correlation with instances of cloud applications, such as cloud application instance 160. The primary purpose of cache service system 156 is to increase data retrieval performance by reducing the need to access the underlying slower physical storage resources the database 162 is instantiated on. In contrast, the larger physical storage resources the database 162 is instantiated on stores data that is usually complete and durable.
Each cloud cache service node includes one or more cloud cache service instances (CCSIs). For example, cloud cache service node 240 includes cloud cache service instances 220, 222, and 224. For simplicity of illustration,
When the cloud application user 204 uses a web browser or mobile application of a client device to read or edit the word document, cloud cache user operations (e.g., related to fetching or modifying cached data) are sent to the cloud cache service instance associated with the cloud application instance, which will locate the memory space associated with the cloud cache service instance.
Cloud cache service system may also process cloud cache management operations through cloud cache service manager 206. Cloud cache service manager 206 may run on one or more physical machines 114 or one or more VMs 118 of the cloud 100. Cloud cache service manager 206 may receive cloud cache management operations from cloud administrator 202. Cloud cache service manager 206 may then send the cloud cache management requests containing the cloud cache management operations to corresponding one or more cloud cache service instances. Examples of cloud cache management operations include, but are not limited to backup, restore, and migration of cached data. For example, cloud administrator user 202 may want to backup data associated with cloud cache service instances 222 and 224. After cloud cache service manager 206 receives the requests for such cloud cache management operations, cloud cache service manager 206 may forward the requests to cloud cache service instances 222 and 224 to start the backup process.
In conventional cloud cache service systems, there is no appropriate coordination among cloud cache user operations, cloud cache management operations, and service attributes of cloud cache service instances. The performance (e.g., response time) of cloud cache user operations could get seriously impacted by cloud cache management operations because cloud cache management operations often require operating on a huge amount of data (e.g., backup, restore, or migration). In addition, different cloud cache service instances in a cloud cache service node have their own separate memory spaces to handle concurrent requests from cloud cache management operations and cloud cache user operations. The approach of a separate memory space for each individual cloud cache service instance does not efficiently utilize memory resources on a cloud cache service node.
For example, there are several technical limitations related to the conventional cloud cache service system 200 illustrated in
The second technical issue is resource utilization efficiency. As illustrated in
Accordingly, technical solutions are needed for improving performance and enhance resource utilization of a cloud cache service system.
To solve the above technical problems, embodiments of this disclosure provide a technical solution in which a cloud cache service system includes a cloud cache service controller (CCSC) between the cloud cache service manager (CCSM) and cloud cache service instances (CCSIs) on one or more cloud cache service nodes. The cloud cache service controller controls management operations. After receiving a cloud cache management request, the cloud cache service controller may evaluate the cloud cache management operation in the cloud cache management request. The cloud cache service controller may calculate a priority value based on associated service attributes dimensions/levels. The cloud cache service controller then uses the calculated priority value to determine how to control and forward the cloud cache management request including the cloud cache operation to the corresponding cloud cache service instance. By controlling the cloud cache management operations, the cloud cache service controller improves the performance of cloud cache user operations because cloud cache user operations are not impacted by the cloud cache management operations. In addition, the controlling offered by the cloud cache management controller allows different cloud cache service instances in the same cloud cache service node to share the same shared memory space, which results in more efficient utilization of memory resources on the cloud cache service nodes.
When cloud application user 304 uses a web browser or mobile application of a client application to access a word processing application running in the cloud 100 to perform certain operations on the word document, such as document viewing or document editing operations, cloud cache user operations (e.g., related to fetching or modifying cached data) are sent to the cloud cache service instance associated with the cloud application instance, which will located the shared memory space 330.
Cloud cache service manager 306 may run on one or more physical machines 114 or one or more VMs 118 of the cloud 100. Cloud cache service manager 306 may receive cloud cache management operations from administrator 302. Examples of cloud cache management operations include, but are not limited to backup, restore, and migration of cached data.
In contrast to the conventional loud cache service system 200 illustrated in
Cloud cache management controller 308 may evaluate a cloud cache management operation in a cloud cache management request based on the type of the cloud cache management operation. For example, cloud cache management controller 308 may retrieve a set of service attribute dimensions/levels associated with the type of the cloud cache management operation. All the service attribute dimensions/levels may be permanently stored in cloud cache service database 310. Before receiving any cloud cache management operation, cloud cache management controller 308 may collect all the service attribute dimensions/levels 312 from cloud cache service database 310. In one example, cloud cache management controller 308 may collect all the service attribute dimensions/levels 312 from cloud cache service database 310 at the startup time. In addition, cloud cache management controller 308 may periodically send collection requests to cloud cache service database 310 so that cloud cache management controller 308 may receive the most recent updates about the attribute dimensions/levels.
Cloud cache service system 300 has multiple dimensions, which are used for describing different service-level agreements (SLAs) for the cloud caching service 124. An SLA may have a functional requirement, which defines a function of the system or its components. A function may be described as a set of inputs, the behavior, and the outputs. An SLA may also have a non-functional requirement, which specifies criteria that can be used to judge the operation of the system, rather than specific behaviors. The system refers to a computer system (e.g., software and/or hardware) in terms of defining functional/non-functional requirements. The system may be the cloud caching system 300 or a cloud system based on the cloud computing architecture 100.
Examples of dimensions include, but are not limited to, service plans for the application platform services 122, including the cloud caching service 124, time elapse entering the next maintenance time, time elapse exiting from the previous maintenance time, operation execution length projection, resource consumption projection. Each dimension may be assigned a weight. The total weight added up for all the dimensions in the system is 100%. For example, the system may have three dimensions. The dimension for service plans may have a weight of 60%, the dimension for time elapse entering the next maintenance time may have a weight of 30%, and the dimension for time elapse exiting may have a weight of 10%.
Each dimension may have one or more levels. A level may have a rank. In one example, the rank may range from 1 to 10. The higher the rank is, the higher the SLA is assigned to a dimension. For example, the system may have three levels of service plans. Level 1 is for a VIP customer plan. Level 2 is for a dedicated customer plan. Level 3 is for a pay-as-you-go customer plan. Different ranks may be assigned to different service plans to indicate the relative importance of one service plan with respect to other service plans. For example, the rank for the VIP customer plan may be 10. The rank for the dedicated customer plan may be 6. The rank for the pay-as-you-go customer plan may be 3.
Based on the retrieved service attribute dimensions/levels, cloud cache management controller 308 may calculate a priority value for a cloud cache management operation. Cloud cache management controller 308 uses the priority value to determine how to control and forward the cloud cache management request to one or more corresponding cloud cache service instances. The priority value may be an overall rank calculated based on the weight and one or more levels associated with each dimension of the dimensions. For example, if there are N dimensions, and each dimension has one level. The priority value may be calculated based on the following.
Priority Value=Dimension1.level*Weight1+Dimension2.level*Weight2+ . . . +DimensionN.level*WeightN.
In the above example, Dimensioni.level represents the rank of the level for Dimensioni, and Weighti represents the weight associated with Dimensioni.
When a dimension has multiple levels, the rank for each level may be considered for calculating the priority value. For example, if there are N dimensions, and each dimension has one level except that the first dimension has two levels. The priority value may be calculated based on the following.
Priority Value=Dimension1.level1*Weight1+Dimension1.level2*Weight1+Dimension2.level*Weight2+ . . . +DimensionN level*WeightN.
In the above example, Dimensioni level represents the rank of the level for Dimensioni (except Dimension1), and Weighti represents the weight associated with Dimensioni. In addition, Dimension1 level1 represents the rank of the first level for Dimension1, and Dimension1.level2 represents the rank of the second level for Dimension1.
After calculating the priority value, cloud cache management controller 308 may determine how to control the cloud cache management operation based on the priority value. For example, cloud cache management controller 308 may delay forwarding the cloud cache management operation to a corresponding cloud cache service instance until the next maintenance time window. In another non-limiting example, cloud cache management controller 308 may calculate priority values for multiple cloud cache management operations and reorder the cloud cache management operations. Cloud cache management controller 308 may forward a cloud cache management operation with a higher priority value before forwarding another cloud cache management operation with a lower priority value.
To trigger a cloud cache management operation, such as backup, restore, or migration, an administrator may use a graphical user interface on her/his administration computing device 402 for initiating the cloud cache management operation. In another embodiment, the management operation may be initiated automatically by a cloud cache management software program running on administration computing device 402, without any user interaction. The administration computing device 402 then sends a cloud cache management request including the cloud cache management operation to cloud cache service manager (CCSM) 404. Rather than directing forwarding the management request to the corresponding cloud cache service instance (CCSI) 410, CCSM 404 forwards the cloud cache management request including the cloud cache management operation to cloud cache management controller (CCMC) 406.
After CCMC 406 receives the cloud cache management request from CCSM 404, CCMC 406 evaluates the cloud cache management request to determine the management operation type of the cloud cache management operation in the cloud cache management request. A management operation type may be, but not limited to, one of a backup, restore, or migration. Based on the management operation type, CCMC 406 calculates a priority value for the cloud cache management operation. For example, CCMC 406 may retrieve a set of service attribute dimensions/levels associated with the type of the cloud cache management operation. The priority value may be an overall rank that CCMC 406 calculates based on the weight and one or more levels associated with each dimension of the dimensions in the retrieved set of service attribute dimensions/levels.
After calculating the priority value, CCMC 406 uses the priority value to determine how to control and forward the cloud cache management request to CCSI 410. CCMC 406 may delay until a next maintenance time window to forward the cloud cache management request to CCSI 410 based on the calculated priority value. In another embodiment, CCMC 406 may receive multiple cloud cache management requests including multiple cloud cache management operations for one or more CCSIs. CCMC 406 may calculate a priority value for each of the multiple cloud cache management operations. CCMC 406 then reorder the multiple cloud cache management requests based on the calculated priority values and forward the multiple cloud cache management requests based on the reordering.
CCMC 406 sends a cloud cache management request to CCSI 410, and the cloud cache management request indicates to CCSI 410 to start the cloud cache management operation included in the cloud cache management request. Based on the cloud cache management operation, CCSI 410 locates shared memory space (SMS) 412. After locating SMS 412, CCSI 410 performs the cloud cache management operation. Afterwards, CCSI sends an operation completion response back to CCMC 406 to indicate that the requested cloud cache management operation has been successfully completed. Then, CCMC 406 forwards the operation completion response back to CCSM 404, which in turn sends the operation completion response to administration computing device 402.
Method 500 starts at operation 502, where the cloud cache management controller may receive multiple sets of service attributes. The cloud cache management controller may run on computing resources of a cloud. Each set of the multiple sets of service attributes may be related to a cloud cache service instance (CCSI). The multiple sets of service attributes may be all the service attributes stored in cloud cache service database 162. At operation 504, the cloud cache management controller may receive a first cloud cache management request comprising a cloud cache management operation. The cloud cache management request may comprise a cloud cache management operation.
At operation 506, the cloud cache management controller may retrieve a set of service attributes from the multiple sets of service attributes based on an evaluation of the cloud cache management operation. In one embodiment, to evaluate the cloud cache management operation, the cloud cache management controller may determine a management type of the cloud cache management operation. The management type of the cloud cache management operation may comprise one of backup, restore, or migration. Then, the cloud cache management controller may retrieve the set of service attributes of the multiple sets of service attributes based on the determined management type. The retrieved set of service attributes may be associated with a corresponding CCSI.
The retrieved set of service attributes may comprise a plurality of dimensions associated with the corresponding CCSI. Each dimension of the plurality of dimensions may correspond to a different service-level agreement (SLA) for the cloud caching service 124. The plurality of dimensions may comprise at least one of a dimension for service plans for the cloud caching service 124, a dimension for a time elapse entering a next maintenance time, a dimension for a time elapse exiting from a previous maintenance time, a dimension for an operation length projection, or a dimension for a resource consumption projection. In addition, each dimension of the plurality of dimensions may be associated with a weight and one or more service plan levels. In one embodiment, the sum of the weight associated with the each of the plurality of dimensions equals to 100%.
At operation 508, the cloud cache management controller may send the first cloud cache management request to a corresponding CCSI based on a priority value for the first cloud cache management request. The priority value may be calculated based on the retrieved set of service attributes. In one embodiment, the cloud cache management controller may calculate the priority value for the cloud cache management request based on the weight and the one or more levels associated with the each dimension of the plurality of dimensions associated with the retrieved set of service attributes.
In one embodiment, the cloud cache management controller may delay until a next maintenance time window to send the first cloud cache management request to the corresponding CCSI based on the priority value.
In another embodiment, the cloud cache management controller may order multiple cloud cache management requests based on calculated priority values associated with the respective cloud cache management requests. For example, the cloud cache management controller may receive a second cloud cache management request after receiving a first cloud cache management request. The second cloud cache management request may comprise a second cloud cache management operation. The cloud cache management controller may then retrieve a second set of service attributes from the multiple sets of service attributes based on a second evaluation of the second cloud cache management operation. Next, the cloud cache management controller may calculate a second priority value for the second cloud cache management request based on the retrieved second set of service attributes. The cloud cache management controller may order the first cloud cache management request and the second cloud cache management request based on the first priority value for the first cloud cache management request and the second priority value for the second cloud cache management request. For example, if the second priority value is higher than the first priority value, the second cloud cache management request may be placed before the first cloud cache management request. The cloud cache management controller may then send the first cloud cache management request and the second cloud cache management request to one or more corresponding cloud cache service instances based on the ordering.
In some embodiments, the processing system 600 is included in a network device that is accessing, or part otherwise of, the one or more networks 154. In other embodiments, the processing system 600 is in a client device accessing the cloud 100 via the one or more networks 154. The client device may be a mobile communication device (e.g., a smartphone), a user equipment (UE), a personal computer (PC), a tablet, a wearable communications device (e.g., a smartwatch, etc.), or any other client device adapted to access the cloud 100 via the one or more networks 154.
As described above, the disclosed cloud cache service controller controls cloud cache management operations and shared memory spaces based on priority values. Controlling cloud cache management operations provides two main technical benefits over the conventional cloud cache service systems. First, the performance of cloud cache user operations is improved because cloud cache user operations are not impacted by the cloud cache management operations. Second, different cloud cache service instances in the same cloud cache service node can share the same shared memory space. Such sharing more efficiently utilizes resources of the cloud cache service nodes.
Although this invention has been described with reference to illustrative embodiments, this description is not intended to be construed in a limiting sense. Various modifications and combinations of the illustrative embodiments, as well as other embodiments of the invention, will be apparent to persons skilled in the art upon reference to the description. It is therefore intended that the appended claims encompass any such modifications or embodiments.
This application is a continuation of International Patent Application No. PCT/CN2018/090152, filed on Jun. 6, 2018, which is hereby incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
8261026 | Klems | Sep 2012 | B2 |
8701109 | Lazier | Apr 2014 | B1 |
9047124 | Mehta | Jun 2015 | B2 |
9098214 | Vincent | Aug 2015 | B1 |
9134980 | Cabrera | Sep 2015 | B1 |
9250863 | Vincent | Feb 2016 | B1 |
9338308 | Adams, Jr | May 2016 | B1 |
9413819 | Berg | Aug 2016 | B1 |
9451013 | Roth | Sep 2016 | B1 |
9569475 | Hoang | Feb 2017 | B2 |
9639546 | Gorski | May 2017 | B1 |
9672054 | Gupta | Jun 2017 | B1 |
10025718 | Wasiq | Jul 2018 | B1 |
10120734 | Doraiswamy | Nov 2018 | B1 |
10176033 | Wang | Jan 2019 | B1 |
10459750 | Zhang | Oct 2019 | B2 |
10628394 | Gurspan | Apr 2020 | B1 |
10853111 | Gupta | Dec 2020 | B1 |
10936545 | Chockalingam | Mar 2021 | B1 |
10972355 | Bauer | Apr 2021 | B1 |
20060028979 | Levesque | Feb 2006 | A1 |
20060056618 | Aggarwal | Mar 2006 | A1 |
20070123297 | Chan | May 2007 | A1 |
20090046094 | Hamilton, II | Feb 2009 | A1 |
20090046102 | Hamilton, II | Feb 2009 | A1 |
20090046109 | Hamilton, II | Feb 2009 | A1 |
20090190475 | Chen | Jul 2009 | A1 |
20090316578 | Mang | Dec 2009 | A1 |
20100299553 | Cen | Nov 2010 | A1 |
20100318575 | Murphy | Dec 2010 | A1 |
20110069666 | Kahn | Mar 2011 | A1 |
20120191834 | Song | Jul 2012 | A1 |
20120221768 | Bagal | Aug 2012 | A1 |
20120260256 | De Faria | Oct 2012 | A1 |
20130013729 | Bennett | Jan 2013 | A1 |
20130097680 | Bendapudi | Apr 2013 | A1 |
20130159451 | Luciw | Jun 2013 | A1 |
20130191842 | Sripathi Panditharadhya | Jul 2013 | A1 |
20130208589 | Lopez Toledo | Aug 2013 | A1 |
20130254325 | Song | Sep 2013 | A1 |
20140013072 | Liu | Jan 2014 | A1 |
20140067990 | Abdelhameed | Mar 2014 | A1 |
20140101237 | Chan et al. | Apr 2014 | A1 |
20140136801 | Birkestrand | May 2014 | A1 |
20140195689 | Gill | Jul 2014 | A1 |
20140279329 | Dancel | Sep 2014 | A1 |
20140280493 | Ortiz Rodriguez | Sep 2014 | A1 |
20140310437 | Saund | Oct 2014 | A1 |
20140344471 | Valko | Nov 2014 | A1 |
20140379409 | Giraldo | Dec 2014 | A1 |
20150006733 | Khan | Jan 2015 | A1 |
20150074285 | Gahm | Mar 2015 | A1 |
20150154713 | Diaz | Jun 2015 | A1 |
20150215791 | Geller | Jul 2015 | A1 |
20150257050 | Karimli | Sep 2015 | A1 |
20160019147 | Vekiarides | Jan 2016 | A1 |
20160019148 | Vekiarides | Jan 2016 | A1 |
20160092803 | Boyacigiller | Mar 2016 | A1 |
20160170893 | Bhogal | Jun 2016 | A1 |
20160173636 | Wang | Jun 2016 | A1 |
20160269501 | Usgaonkar | Sep 2016 | A1 |
20160274929 | King | Sep 2016 | A1 |
20160321288 | Malhotra | Nov 2016 | A1 |
20160350091 | Khot et al. | Dec 2016 | A1 |
20160378546 | Brouwer | Dec 2016 | A1 |
20160378547 | Brouwer | Dec 2016 | A1 |
20170046143 | Kochhar | Feb 2017 | A1 |
20170078216 | Adolph | Mar 2017 | A1 |
20170124000 | Ash | May 2017 | A1 |
20170249310 | Kumar | Aug 2017 | A1 |
20170289593 | Li | Oct 2017 | A1 |
20170308622 | Thornburgh | Oct 2017 | A1 |
20170344481 | Pack, III | Nov 2017 | A1 |
20170344484 | Pack, III | Nov 2017 | A1 |
20170351549 | Burke | Dec 2017 | A1 |
20170366606 | Ben-Shaul | Dec 2017 | A1 |
20180004667 | Xiang | Jan 2018 | A1 |
20180007106 | Racz | Jan 2018 | A1 |
20180019985 | Schoof | Jan 2018 | A1 |
20180039628 | de Lavarene | Feb 2018 | A1 |
20180060182 | Rao Kotha | Mar 2018 | A1 |
20180136960 | Zhang | May 2018 | A1 |
20180137114 | Barbas | May 2018 | A1 |
20180191550 | Vempati | Jul 2018 | A1 |
20180249015 | Nakano | Aug 2018 | A1 |
20180300242 | Liu | Oct 2018 | A1 |
20180365036 | Toal | Dec 2018 | A1 |
20190065560 | Rojkov | Feb 2019 | A1 |
20190095253 | Curtis | Mar 2019 | A1 |
20190104030 | Giust | Apr 2019 | A1 |
20190130327 | Carpenter | May 2019 | A1 |
20190158354 | Zhou | May 2019 | A1 |
20190179755 | Mudumbai | Jun 2019 | A1 |
20190213230 | Lu | Jul 2019 | A1 |
20190310880 | Gupta | Oct 2019 | A1 |
20190378071 | Xu | Dec 2019 | A1 |
20200084121 | Matray | Mar 2020 | A1 |
20200159561 | Zhang | May 2020 | A1 |
20200358672 | Lange | Nov 2020 | A1 |
20220021590 | Seetharaman | Jan 2022 | A1 |
Number | Date | Country |
---|---|---|
102739771 | Oct 2012 | CN |
104854567 | Aug 2015 | CN |
106131158 | Nov 2016 | CN |
107346307 | Nov 2017 | CN |
107493327 | Dec 2017 | CN |
Entry |
---|
H. He, Z. Ma, H. Chen, D. Wu, H. Liu and W. Shao, “An SLA-Driven Cache Optimization Approach for Multi-tenant Application on PaaS,” 2014 IEEE 38th Annual Computer Software and Applications Conference, 2014, pp. 139-148, doi: 10.1109/COMPSAC.2014.21. (Year: 2014). |
M. Claeys et al., “Proactive multi-tenant cache management for virtualized ISP networks,” 10th International Conference on Network and Service Management (CNSM) and Workshop, 2014, pp. 82-90, doi: 10.1109/CNSM.2014.7014144. (Year: 2014). |
Claeys, Maxim, et al. “Hybrid multi-tenant cache management for virtualized ISP networks.” Journal of Network and Computer Applications 68 (2016): 28-41. (Year: 2016). |
Stefanovici, loan, et al. “Software-defined caching: Managing caches in multi-tenant data centers.” Proceedings of the Sixth ACM Symposium on Cloud Computing. 2015. (Year: 2015). |
Y. Xiang, T. Lan, V. Aggarwal and Y.-F. Chen, “Optimizing Differentiated Latency in Multi-Tenant, Erasure-Coded Storage,” in IEEE Transactions on Network and Service Management, vol. 14, No. 1, pp. 204-216, Mar. 2017, doi: 10.1109/TNSM.2017.2658440. (Year: 2017). |
Number | Date | Country | |
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20200344110 A1 | Oct 2020 | US |
Number | Date | Country | |
---|---|---|---|
Parent | PCT/CN2018/090152 | Jun 2018 | US |
Child | 16920841 | US |