Method and system for exploiting service level objectives to enable resource sharing in a communication network having a plurality of application environments

• US 7,310,672 B2
• Filed: 11/13/2001
• Issued: 12/18/2007
• Est. Priority Date: 11/13/2001
• Status: Expired due to Fees

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Rolia, Jerome
• Primary Examiner(s): Vaughn; William
• Assistant Examiner(s): SHINGLES, KRISTIE D
• Application Number:
  US09/991,339
• Publication Number:
  US 20030093527A1
• Time in Patent Office: 2,226 Days
• Field of Search: 709/104, 709/200, 709/201, 709/224, 709/226, 709/229, 709/223, 703/2, 703/13, 703/22
• US Class Current: 709/226
• CPC Class Codes: G06F 2209/5019 Workload prediction
• CPC Class Codes: G06F 9/50 Allocation of resources, e.g. of the central processing unit [CPU]
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/10015 Access to distributed or replicated servers, e.g. using brokers
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 9/40 Network security protocols

Abstract

A method and system for resource sharing in a communication network supporting a plurality of application environments. Specifically, one embodiment of the present invention discloses a method ensuring only sufficient computational resources are used by a multi-component system as needed to meet system, subsystem, and/or component-level service level objectives. Demand values are calculated for a plurality of components in an application environment. The demand values are calculated from throughput and utilization metrics collected at each of the plurality of components. Response time metrics are predicted from the demand values. The application environment is modeled in response to the response time metrics to determine the optimum number of computational resources needed for each of the components in satisfying a functional objective. A dynamic resource manager communicates with a plurality of component managers, one for each of the plurality of components, to allocate computational resources throughout the application environment.

Claims

1. A method of resource allocation comprising:

a) calculating a plurality of demand values for a plurality of components, wherein said plurality of demand values is calculated from a combination of throughput and utilization metrics, wherein said components are communicatively coupled in series, wherein processing of a request from a user received at a first component of said plurality of components proceeds forward through said components to a last component in said series and then backward through said components to said first component and then to said user, wherein a performance of service is suspended at each of said components after said processing of a request by said each of said components, and wherein said metrics are measurable at points between said components;

b) predicting a plurality of response time metrics for said plurality of components based on said plurality of demand values;

c) modeling said plurality of components based on an objective function that responds to conditions as represented by said plurality of response time metrics when at least one of said plurality of response time metrics does not satisfy at least one of a plurality of service level objectives to determine a new effective distribution of computational resources throughout said plurality of components such that said plurality of components that are modeled satisfies said plurality of service level objectives; and

d) allocating computational resources throughout said plurality of components to reflect said new effective distribution.

2. The method as described in claim 1, wherein said plurality of components comprise an application environment.

3. The method as described in claim 1, wherein said at least one of a plurality of service level objectives applies to said plurality of components on a system-wide basis.

4. The method as described in claim 1, wherein said at least one of a plurality of service level objectives applies to said plurality of components on a subsystem basis.

5. The method as described in claim 1, wherein said at least one of a plurality of service level objectives applies to one of said plurality of components.

6. The method as described in claim 1, wherein a) further comprises:

receiving a plurality of metric values from said plurality of components, said plurality of metric values used to calculate said demand values.

7. The method as described in claim 1, wherein c) comprises:

inputting said plurality of demand values into a predictive model to determine said new effective distribution of computational resources.

8. The method as described in claim 1, wherein d) comprises:

removing computational resources from said plurality of components.

9. The method as described in claim 1, wherein d) comprises:

adding computational resources to said plurality of components.

10. A method of resource allocation in an application environment comprising:

a) receiving a plurality of metric values from a plurality of components of said application environment, wherein said components are communicatively coupled in series, wherein processing of a request from a user received at a first component of said plurality of components proceeds forward through said components to a last component in said series and then backward through said components to said first component and then to said user, wherein a performance of service is suspended at each of said components after said processing of a request by said each of said components, and wherein said metric values are measurable at points between said components;

b) calculating a plurality of demand values from said plurality of metric values;

c) predicting a plurality of response time metrics for each of said plurality of components based on said plurality of demand values;

d) modeling said plurality of components based on an objective function that responds to conditions as represented by said plurality of response time metrics when at least one of said plurality of response time metrics does not satisfy at least one of a plurality of service level objectives applying to said plurality of components on a system level to determine a new effective distribution of computational resources for said plurality of components such that response time metrics associated with said plurality of components that are modeled satisfies said plurality of service level objective, wherein said new effective distributions results in an optimum number of said plurality of components; and

e) allocating computational resources throughout said plurality of components to reflect said optimum number.

11. The method of resource allocation as described in claim 10, wherein d) further comprises:

determining a plurality of optimum numbers of computational resources, one for each of said plurality of components, that represents said new effective distribution of computational resources.

12. The method of resource allocation as described in claim 10, wherein e) comprises:

removing computational resources from said plurality of components.

13. The method as described in claim 10, wherein e) comprises:

adding computational resources to said plurality of components.

14. The method as described in claim 10, wherein c) comprises:

predicting said plurality of response time metrics using a prediction modeling technique.

15. The method as described in claim 14, wherein said plurality of metric values includes throughput metrics and utilization metrics.

16. The method as described in claim 10, wherein c) comprises:

inputting said plurality of demand values into a predictive model to determine said optimum number.

17. A computer system comprising:

a processor;

a computer readable memory coupled to said processor and containing program instructions that, when executed, implement a method of resource allocation comprising;

a) calculating a plurality of demand values for a plurality of components, wherein said plurality of demand values is calculated from a combination of throughput and utilization metrics, wherein said components are communicatively coupled in series, wherein processing of a request from a user received at a first component of said plurality of components proceeds forward through said components to a last component in said series and then backward through said components to said first component and then to said user, wherein a performance of service is suspended at each of said components after said processing of a request by said each of said components, and wherein said metrics are measurable at points between said components;

b) predicting a plurality of response time metrics for said plurality of components based on said plurality of demand values;

c) modeling said plurality of components based on an objective function that responds to conditions as represented by said plurality of response time metrics when at least one of said plurality of response time metrics does not satisfy at least one of a plurality of service level objectives to determine a new effective distribution of computational resources throughout said plurality of components such that said plurality of components that are modeled satisfies said plurality of service level objectives; and

d) allocating computational resources throughout said plurality of components to reflect said new effective distribution.

18. The computer system as described in claim 17, wherein said plurality of components comprise an application environment.

19. The computer system as described in claim 17, wherein said at least one of a plurality of service level objectives applies to said plurality of components on a system-wide basis.

20. The computer system as described in claim 17, wherein said at least one of a plurality of service level objectives applies to said plurality of components on a subsystem basis.

21. The computer system as described in claim 17, wherein said at least one of a plurality of service level objectives applies to one of said plurality of components.

22. The computer system as described in claim 17, wherein a) in said method of resource allocation further comprises:

receiving a plurality of metric values from said plurality of components, said plurality of metric values used to calculate said demand values.

23. The computer system as described in claim 17, wherein c) in said method of resource allocation comprises:

inputting said plurality of demand values into a predictive model to determine said new effective distribution of computational resources.

24. The computer system as described in claim 17, wherein d) in said method of resource allocation comprises:

removing computational resources from said plurality of components.

25. The computer system as described in claim 17, wherein d) in said method of resource allocation comprises:

adding computational resources to said plurality of components.

26. A communication network comprising:

a plurality of computational resources;

an application environment having a plurality of network nodes coupled together;

a plurality of components in said application environment servicing an application, each of said plurality of components including at least one computational resource from said plurality of computational resources, each of said plurality of components residing on one of said plurality of network nodes, wherein said components are communicatively coupled in series, wherein processing of a request from a user received at a first component of said plurality of components proceeds forward through said components to a last component in said series and then backward through said components to said first component and then to said user, wherein a performance of service is suspended at each of said components after said processing of a request by said each of said components;

a plurality of metrics measured at each of said plurality of components for calculating a plurality of demand values, wherein said metrics are measurable at points between said components, wherein said plurality of demand values is calculated from a combination of throughput and utilization metrics;

a functional objective for defining an optimum number of computational resources in said application environment; and

a dynamic resource manager coupled to said application environment for modeling said plurality of components based on said functional objective that responds to conditions as represented by said plurality of demand values when at least one of said plurality of demand values does not satisfy at least one of a plurality of service level objectives to determine a new effective distribution of computational resources throughout each of said plurality of components such that said plurality of components that are modeled satisfies said plurality of service level objectives.

27. The communication network as described in claim 26, wherein said plurality of metrics comprises throughput metrics and utilization metrics.

28. The communication network as described in claim 26, further comprising:

a prediction model for predicting a plurality of response time metrics for said plurality of components based on said plurality of demand values; and

a mathematical model for modeling said plurality of components in response to said plurality of response time metrics for determining said new effective distribution of computational resources.

29. The communication network as described in claim 26, further comprising:

a plurality of component managers, one for each of said plurality of components, for managing the addition and removal of computational resources in said plurality of components in response to notices from said dynamic resource manager.

30. The communication network as described in claim 26, wherein said plurality of components comprise a local area network (LAN).