Policy driven autonomic computing-specifying relationships

• US 20050091352A1
• Filed: 09/30/2003
• Published: 04/28/2005
• Est. Priority Date: 09/30/2003
• Status: Active Grant

• Current Assignee: Trend Micro Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Schneider, Juergen, Badovinatz, Peter R., Chang, Chun-Shi, Lucash, Jeffrey S., Lumpp, Thomas, Buendgen, Reinhard, Lee, Rong-Sheng, Laib, Gregory D., Alex, John K.
• Granted Patent: US 7,451,201 B2
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: H04L 41/0661 by reconfiguring faulty entities
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 43/0817 by checking functioning

Abstract

An autonomic computing system and method determine policy definitions (404) and a set of available actions (410); monitor resources distributed within the system; determine if the system is at a desired end state; and modify resource states by sending instructions for the resources to perform available actions. The policy definitions (404) specify: start order between resources, prioritization between resources, conditional activation of policies, desired end state of resources, and location limitation of resources. The system and method receive status information from available resources, and monitor and modify the system until it reaches the desired end state. The policy definitions (404) can be determined by specifying a user-defined system end state and resource relationships. The policy definitions (404) can further harvest implicit relationships between resources, via self-discovery, and underlying relationships among resources.

Claims

1. A method comprising:

determining policy definitions for an autonomic computing system;

monitoring applicable resources for status information;

determining if the autonomic computing system is at a desired end state; and

modifying resource states, by sending all instruction for the resource to perform an available action, in response to determining the autonomic computing system is not at the desired end state.

2. The method of claim 1, wherein the policy definitions can specify at least one of:

an association between a resource and any other set of resources; and

a desired state for a resource or set of resources.

3. The method of claim 2, wherein the association between a resource and any other set of resources comprise at least one of:

a start order among resources;

a stop order among resources;

a prioritization between resources;

a conditional activation of policies; and

a location limitation of resources.

4. The method of claim 1, further comprising:

receiving resource status information from available resources; and

continuing to determine if the autonomic computing system is at the desired end state and modifying the resource states, by sending an instruction for the resource to perform an available action, until the autonomic computing system has reached the desired end state.

5. The method of claim 1, wherein the determining policy definitions for an autonomic computing system comprises:

determining a user-defined system end state; and

determining a set of user-defined resource relationships.

6. The method of claim 1, wherein the determining policy definitions for an autonomic computing system further comprises harvesting implicit relationships between resources through self discovery.

7. The method of claim 1, wherein the determining policy definitions for an autonomic computing system further comprises determining underlying relationships among members of a resource group.

8. The method according to claim 7, wherein the members of the resource group are distributed within a heterogeneous cluster.

9. A computer readable medium comprising computer instructions for performing the following:

determining policy definitions for an autonomic computing system;

monitoring applicable resources for status information;

determining if the autonomic computing system is at a desired end state; and

modifying resource states, by sending an instruction for a resource to perform an available action, in response to determining the autonomic computing system is not at the desired end state.

10. The computer readable medium of claim 9, wherein the policy definitions can specify at least one of:

an association between a resource and any other set of resources; and

a desired end state for a resource or set of resources.

11. The computer readable medium of claim 10, wherein the association between a resource and any other set of resources comprise at least one of:

a start order among resources;

a stop order among resources;

a prioritization between resources;

a conditional activation of policies; and

a location limitation of resources.

12. The computer readable medium of claim 9, further comprising computer instructions for performing the following:

receiving resource status information from available resources; and

continuing to determine if the autonomic computing system is at a desired end state and modifying the resource states, by sending an instruction for a resource to perform an available action, until the autonomic computing system has reached a desired end state.

13. The computer readable medium of claim 9, wherein the determining policy definitions for an autonomic computing system comprises:

determining a user-defined system end state; and

determining a set of user-defined resource relationships.

14. The computer readable medium of claim 9, wherein the determining policy definitions for an autonomic computing system further comprises harvesting implicit relationships between resources through self discovery.

15. The computer readable medium of claim 9, wherein the determining policy definitions for an autonomic computing system further comprises determining underlying relationships among members of a resource group.

16. The computer readable medium according to claim 15, wherein the members of the resource group are distributed within a heterogeneous cluster.

17. An autonomic computing system resource manager comprising:

memory for storing at least one policy definition;

a resource monitor, communicatively coupled with at least one resource in an autonomic computing system and with the memory, for monitoring, and communicating data with, the at least one resource;

a policy generator, communicatively coupled with the memory, and with the resource harvester, for providing in the memory a representation of a system-wide graph of available actions corresponding with the at least one resource in the autonomic computing system; and

an automation engine;

communicatively coupled to the resource monitor and the memory, for communicating available actions to the at least one resource in order for the autonomic computing system to establish and maintain a desired end state.

18. The autonomic computing system resource manager of claim 17, further comprising:

a resource harvester, communicatively coupled with the at least one resource, the resource monitor, and the policy generator, for harvesting implicit relationships between resources in the autonomic computing system via self discovery.

19. The autonomic computing system resource manager of claim 17, wherein:

the policy generator further for specifying implicit relationships between resources in the autonomic computing system.

20. The autonomic computing system resource manager of claim 19, wherein the policy generator further for specifying implicit relationships between resources that are distributed within a heterogeneous cluster in the autonomic computing system.

21. The autonomic computing system resource manager of claim 17, wherein:

the policy generator for creating at least one policy definition specified at least in part by a user of the autonomic computing system.

22. The autonomic computing system resource manager of claim 17, wherein:

the policy generator for creating at least one policy definition determined at least in part by autonomic computing system self discovery.

23. An apparatus comprising:

a cluster resource manager, for determining policy definitions for an autonomic computing system, determining a set of available actions, monitoring at least one resource in the autonomic computing system for status information, determining if the autonomic computing system is at a desired end state, and modifying resource states of the at least one resource, by sending at least one instruction for the at least one resource to perform an available action, in response to determining the autonomic computing system is not at the desired end state; and

at least one network interface card, communicatively coupled with the cluster resource manager and the at least one resource, for communicating information between the cluster resource manager and the at least one resource in the autonomic computing system.

24. An autonomic computing system comprising:

at least one distributed resource; and

an autonomic computing system resource manager comprising;

memory for storing at least one policy definition;

a resource monitor, communicatively coupled with at least one resource in an autonomic computing system and with the memory, for monitoring, and communicating data with, the at least one resource;

a policy generator, communicatively coupled with the memory, and with the resource harvester, for providing in the memory a representation of a system-wide graph of available actions corresponding with the at least one distributed resource in the autonomic computing system; and

an automation engine, communicatively coupled with the resource monitor and the memory, for communicating available actions to the at least one distributed resource in order for the autonomic computing system to establish and maintain a desired end state.