Planned cloud resource management

• US 10,606,660 B1
• Filed: 05/01/2017
• Issued: 03/31/2020
• Est. Priority Date: 04/29/2016
• Status: Active Grant

• Current Assignee: Architectural technology Inc.
• Original Assignee: Architecture Technology Corporation
• Inventors: Hartley, Timothy E., Ramanujan, Ranga S.
• Primary Examiner(s): Sison, June Y
• Assistant Examiner(s): Cooney, Adam A
• Application Number:
  US15/583,692
• Time in Patent Office: 1,065 Days
• Field of Search: 709226
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 2009/45579 I/O management, e.g. providing access to device drivers or storage
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/5066 Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs mappping at compile time, see G06F8/451
• CPC Class Codes: G06F 9/5077 Logical partitioning of resources; Management or configuration of virtualized resources specific details on emulation or internal functioning of virtual machines G06F9/455
• CPC Class Codes: G06F 9/5083 Techniques for rebalancing the load in a distributed system
• CPC Class Codes: H04L 12/4641 Virtual LANs, VLANs, e.g. virtual private networks [VPN] LAN interconnection over a bridge based backbone H04L12/462; encapsulation techniques H04L12/4633; routing of packets H04L45/00; packet switches H04L49/00; virtual private networks for security H04L63/0272
• CPC Class Codes: H04L 41/0806 for initial configuration or provisioning, e.g. plug-and-play
• CPC Class Codes: H04L 41/0895 Configuration of virtualised networks or elements, e.g. virtualised network function or OpenFlow elements
• CPC Class Codes: H04L 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 41/20 Network management software packages
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 41/50 Network service management, e.g. ensuring proper service fulfilment according to agreements
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/20 the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 45/74 Address processing for routing
• CPC Class Codes: H04L 63/0428 wherein the data content is protected, e.g. by encrypting or encapsulating the payload
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/1004 Server selection for load balancing
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

Abstract

One embodiment is directed to a method of managing hardware resources of a plurality of client nodes. The method includes providing a plan that indicates when to execute a plurality of applications and identifying one or more concurrent applications which are one or more of the plurality of applications that are scheduled to execute concurrently according to the plan. The method also includes determining which of the one or more concurrent applications to execute on which of a plurality of client nodes by maximizing a utility function that factors in aspects of each of one or more concurrent applications and the hardware resources of the plurality of client nodes. Respective client nodes of the plurality of client nodes are instructed to execute respective applications as determined.

Claims

1. A method of managing hardware resources of a plurality of client nodes, the method comprising:

providing a plan that indicates when to execute a plurality of applications;

identifying one or more concurrent applications which are one or more of the plurality of applications that are scheduled to execute concurrently according to the plan;

generating a plurality of hypothetical execution assignments of the one or more concurrent applications to the plurality of client nodes;

prior to executing at least one of the plurality of hypothetical execution assignments, evaluating the hypothetical execution assignments with a utility function that factors in aspects of each of the one or more concurrent applications and the hardware resources of the plurality of client nodes from a plurality of different profiles, wherein each execution assignment assigns a particular application of the one or more concurrent applications to a particular client node or particular type of client node from the plurality of client nodes; and

instructing respective client nodes of the plurality of client nodes to execute respective applications based on the utility function.

2. The method of claim 1, wherein the utility function factors in one or more of a priority level, a minimum required resource allocation, and one or more desired types of hardware resources for the one or more applications.

3. The method of claim 2, wherein the utility function factors in the different hardware resources of each of the plurality of client nodes.

4. The method of claim 1, comprising:

dynamically repeating the steps of identifying, generating, evaluating, and instructing to update which applications are executing on each client node of the plurality of client nodes over time in accordance with the plan.

5. The method of claim 4, wherein the plan indicates that one or more applications are to be added to a list of authorized application in response to one or more trigger events.

6. The method of claim 5, wherein the one or more trigger events include one or more of a specific time, a relative time, and an item of information received.

7. The method of claim 6, comprising:

receiving the item of information from an application of the plurality of applications while the application is executing on the plurality of client nodes.

8. The method of claim 4, wherein identifying one or more concurrent applications includes identifying one or more applications that are already executing and one or more applications that are not yet executing,

wherein evaluating includes evaluating premature halting of an application that is already executing.

9. The method of claim 4, comprising:

monitoring the plurality of client nodes to identify if hardware resources at any of the client nodes become unavailable for use by the plurality of applications,

wherein the utility function factors in hardware resources that have become unavailable.

10. The method of claim 4, comprising:

monitoring the plurality of client nodes to learn use of hardware resources by one or more applications executing on the plurality of client nodes; and

wherein the utility function factors in the learned use of hardware resources by the one or more applications executing on the plurality of client nodes.

11. The method of claim 1, comprising:

communicating with the plurality of client nodes over a local area network (LAN).

12. The method of claim 1, wherein instructing respective client nodes includes instructing respective client nodes to execute respective applications in accordance with the hypothetical execution assignment that maximizes the utility function.

13. A data storage entity comprising:

a non-transitory processor readable medium having software stored thereon, wherein the software, when executed by one or more processing devices;

identifies one or more concurrent applications which are one or more of a plurality of applications that are scheduled to execute concurrently according to a plan, wherein the plan indicates when to execute the plurality of applications;

generates a plurality of hypothetical execution assignments of the one or more concurrent applications to a plurality of client nodes;

prior to executing at least one of the plurality of hypothetical execution assignments, evaluates the hypothetical execution assignments with a utility function that factors in aspects of each of the one or more concurrent applications and the hardware resources of the plurality of client nodes from a plurality of different profiles, wherein each execution assignment assigns a particular application of the one or more concurrent applications to a particular client node or particular type of client node from the plurality of client nodes; and

instructs respective client nodes of the plurality of client nodes to execute respective applications based on the utility function.

14. The data storage entity of claim 13, wherein the software, when executed by one or more processing devices:

dynamically repeats the identifies, generates, evaluates, and instructs to update which applications are executing on each client node of the plurality of client nodes over time in accordance with the plan.

15. The data storage entity of claim 14, wherein identifies one or more concurrent applications includes identifies one or more applications that are already executing and one or more applications that are not yet executing,

wherein evaluates includes evaluates premature halting of an application that is already executing.

16. The data storage entity of claim 14, wherein the software, when executed by one or more processing devices:

monitors the plurality of client nodes to identify if hardware resources at any of the client nodes become unavailable for use by the plurality of applications,

wherein the utility function factors in hardware resources that have become unavailable.

17. The data storage entity of claim 14, wherein the software, when executed by one or more processing devices:

monitors the plurality of client nodes to learn use of hardware resources by one or more applications executing on the plurality of client nodes; and

wherein the utility function factors in the learned use of hardware resources by the one or more applications executing on the plurality of client nodes.

18. The method of claim 13, wherein instructs respective client nodes includes instructs respective client nodes to execute respective applications in accordance with the hypothetical execution assignment that maximizes the utility function.

19. The data storage entity of claim 18, wherein the utility function factors in one or more of a priority level, a minimum required resource allocation, and one or more desired types of hardware resources for the one or more applications.

20. The data storage entity of claim 19, wherein the utility function factors in the different hardware resources of each of the plurality of client nodes.

21. The data storage entity of claim 19, wherein the plan indicates that respective applications of the plurality of applications are to be execute in response to one or more trigger events,

wherein the one or more trigger events include one or more of a specific time, a relative time, and an item of information received.

22. A network of nodes comprising:

a plurality of client nodes, each client node having one or more processing devices coupled to one or more data storage devices having instructions thereon, wherein the instructions on at least some of the client nodes implement a client manager when executed on the one or more processing devices of the corresponding client node;

a cloud manager node communicatively coupled to the plurality of client nodes, the cloud manager node including one or more processing devices coupled to one or more data storage devices having instructions thereon, wherein the instructions when executed on the one or more processing devices of the client node;

identify one or more concurrent applications which are one or more of a plurality of applications that are scheduled to execute concurrently according to a plan, wherein the plan indicates when to execute the plurality of applications;

generate a plurality of hypothetical execution assignments of the one or more concurrent applications to the plurality of client nodes;

prior to executing at least one of the plurality of hypothetical execution assignments, evaluate the hypothetical execution assignments with a utility function that factors in aspects of each of the one or more concurrent applications and the hardware resources of the plurality of client nodes from a plurality of different profiles; and

instruct client managers of each client node to execute respective applications in accordance with the hypothetical execution assignment that maximizes the utility function.