Modifying computer configuration to improve performance

• US 10,341,164 B2
• Filed: 05/09/2017
• Issued: 07/02/2019
• Est. Priority Date: 05/09/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bonanni, Cristina, Milanese, Nicola, Sidoti, Stefano, Tortosa, Andrea
• Primary Examiner(s): Fan, Hua
• Application Number:
  US15/590,365
• Publication Number:
  US 20180331882A1
• Time in Patent Office: 784 Days
• CPC Class Codes: H04L 41/08 Configuration management of networks or network elements address allocation H04L61/50
• CPC Class Codes: H04L 41/0823 characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for optimising operational conditions of wireless networks H04W24/02
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1012 based on compliance of requirements or conditions with available server resources
• CPC Class Codes: H04L 67/1031 Controlling of the operation of servers by a load balancer, e.g. adding or removing servers that serve requests
• CPC Class Codes: H04L 67/1038 Load balancing arrangements to avoid a single path through a load balancer
• CPC Class Codes: H04L 67/1076 Resource dissemination mechanisms or network resource keeping policies for optimal resource availability in the overlay network
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• 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

Embodiments of the present disclosure relate to improving computer performance. An action may be issued to a first client and a second client. A first optimization factor list (OFL) may be generated for the first client and a second OFL may be generated for the second client. After each OFL is generated, the first OFL may be compared to the second OFL. A correlation factor (CF) may be generated between the first client and the second client based on the OFL comparison, wherein the CF indicates a level of similarity between the first client and the second client. A bottleneck causing performance issues in the first client may be determined and computer configuration of the first client may be adjusted based on the bottleneck.

Claims

1. A method comprising:

issuing, by a processor, an action to a first client and a second client;

generating a first optimization factor list (OFL) for the first client and a second OFL for the second client;

comparing the first OFL to the second OFL;

generating a correlation factor (CF) between the first client and second client based on the OFL comparison, wherein the CF indicates a level of similarity between the first client and the second client, wherein generating the CF includes generating a partial CF value for each factor in the OFL, weighting each factor in the OFL, adjusting each partial CF value using a weight of the factor associated with the partial CF, and accumulating the adjusted partial CF values;

determining that there is a bottleneck causing performance issues in the first client;

adjusting, in response to determining that there is a bottleneck causing performance issues in the first client, a client computer configuration of the first client based on the bottleneck;

generating, by the processor, a relevance factor (RF) based on an adjustment made to a factor of the client computer configuration; and

altering, based on the RF of the adjustment made to the factor of the client computer configuration, the OFL and CF.

2. The method of claim 1, wherein the altering the OFL and CF comprises:

determining that the RF exceeds a threshold RF value; and

increasing, in response to determining that the RF exceeds the threshold RF value, the weighting of the factor that was adjusted.

3. The method of claim 1, wherein the altering the OFL and CF comprises:

determining that the RF does not exceed a threshold RF value; and

decreasing, in response to the RF not exceeding the threshold RF value, the weighting of the factor that was adjusted.

4. The method of claim 3, wherein the altering the OFL and CF comprises:

determining that the weighting of the factor is negligible to the CF determination; and

removing, in response to a determination that the weighting of the factor is negligible to the CF determination, the factor from the OFL.

5. The method of claim 1, the method further comprising:

classifying, by the processor, the first client and the second client into performance efficiency classes based on action performance; and

determining that the first client and the second client are in different performance efficiency classes, wherein the comparing the OFL of the first client to the OFL of the second client is performed in response to determining that the first and second clients are in different performance efficiency classes.

6. The method of claim 1, wherein the comparing the OFL of the first client to the OFL of the second client is performed in response to determining that the first and second clients have the same processor and operating system.

7. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

issuing an action to a first client and a second client;

generating a first optimization factor list (OFL) for the first client and a second OFL for the second client;

comparing the first OFL to the second OFL;

generating a correlation factor (CF) between the first client and second client based on the OFL comparison, wherein the CF indicates a level of similarity between the first client and the second client, wherein generating the CF includes generating a partial CF value for each factor in the OFL, weighting each factor in the OFL, adjusting each partial CF value using a weight of the factor associated with the partial CF, and accumulating the adjusted partial CF values;

determining that there is a bottleneck causing performance issues in the first client;

adjusting in response to determining that there is a bottleneck causing performance issues in the first client, client computer configuration of the first client based on the bottleneck;

generating a relevance factor (RF) based on an adjustment made to a factor of the client computer configuration, wherein a high RF indicates that the adjustment to the factor improved client performance; and

altering, based on the RF of the adjustment made to the factor of the client computer configuration, the OFL and CF.

8. The computer program product of claim 7, wherein the altering the OFL and CF comprises:

determining that the RF exceeds a threshold RF value; and

increasing, in response to the RF exceeding the threshold RF value, the weighting of the factor that was adjusted.

9. The computer program product of claim 7, wherein the altering the OFL and CF comprises:

determining that the RF does not exceed a threshold RF value; and

decreasing, in response to the RF not exceeding the threshold RF value, the weighting of the factor that was adjusted.

10. The computer program product of claim 9, wherein the altering the OFL and CF comprises:

determining that the weighting of the factor is negligible to the CF determination; and

removing, in response to a determination that the weighting of the factor is negligible to the CF determination, the factor from the OFL.

11. The computer program product of claim 7, the method further comprising:

classifying the first client and the second client into performance efficiency classes based on action performance; and

determining that the first client and the second client are in different performance efficiency classes, wherein the comparing the OFL of the first client to the OFL of the second client is performed in response to determining that the first and second clients are in different performance efficiency classes.

12. A system comprising:

a memory storing program instructions on a non-transitory computer-readable medium;

a first client and a second client; and

a processor communicatively coupled to the memory and the first client and the second client, wherein the processor is configured to execute the program instructions to perform a method comprising;

issuing an action to the first client and the second client;

generating a first optimization factor list (OFL) for the first client and a second OFL for the second client;

comparing the first OFL to the second OFL;

generating a correlation factor (CF) between the first client and second client based on the OFL comparison, wherein the CF indicates a level of similarity between the first client and the second client, wherein generating the CF includes generating a partial CF value for each factor in the OFL, weighting each factor in the OFL, adjusting each partial CF value using a weight of the factor associated with the partial CF, and accumulating the adjusted partial CF values;

determining that there is a bottleneck causing performance issues in the first client;

adjusting in response to determining that there is a bottleneck causing performance issues in the first client, client computer configuration of the first client based on the bottleneck;

generating a relevance factor (RF) based on an adjustment made to a factor of the client computer configuration, wherein a high RF indicates that the adjustment to the factor improved client performance; and

altering, based on the RF of the adjustment made to the factor of the client computer configuration, the OFL and CF.

13. The system of claim 12, wherein the altering the OFL and CF comprises:

determining that the RF exceeds a threshold RF value; and

increasing, in response to the RF exceeding the threshold RF value, the weighting of the factor that was adjusted.

14. The system of claim 12, wherein the altering the OFL and CF comprises:

determining that the RF does not exceed a threshold RF value;

decreasing, in response to the RF not exceeding the threshold RF value, the weighting of the factor that was adjusted;

determining that the weighting of the factor is negligible to the CF determination; and

removing, in response to a determination that the weighting of the factor is negligible to the CF determination, the factor from the OFL.

15. The system of claim 12, the method further comprising:

classifying the first client and the second client into performance efficiency classes based on action performance; and

determining that the first client and the second client are in different performance efficiency classes, wherein the comparing the OFL of the first client to the OFL of the second client is performed in response to determining that the first and second clients are in different performance efficiency classes.

16. The system of claim 12, wherein the comparing the OFL of the first client to the OFL of the second client is performed in response to determining that the first and second clients have the same processor, memory, and operating system.