Determining virtual machine image pattern distributions in a networked computing environment
US-9038063-B2 · May 19, 2015 · US
US10353738B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10353738-B2 |
| Application number | US-201213425509-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 21, 2012 |
| Priority date | Mar 21, 2012 |
| Publication date | Jul 16, 2019 |
| Grant date | Jul 16, 2019 |
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Embodiments of the present invention provide an approach for allocating computing resources based on social networking/media trends in a networked computing environment (e.g., a cloud computing environment). In a typical embodiment, a baseline computing resource allocation will be determined for the networked computing environment based upon historical computing resource data (e.g., stored in at least one computer storage device). Social networking trend data corresponding to usage of a set of social networking websites may be received and analyzed to determine a forecasted computing resource allocation (e.g., based on social networking trends). The baseline computing resource allocation may be compared to the forecasted computing resource allocation to identify any difference therebetween. A computing resource allocation protocol/plan may then be determined based on the comparison (e.g., to address the difference).
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method for allocating computing resources based on social networking trends in a networked computing environment, comprising: receiving publically available topic-based social networking trend data that is external to the networked computing environment and corresponds to usage of a set of social networking websites that are unaffiliated with the networked computing environment; grouping messages in the publically available topic-based social networking trend data into a plurality of topic groups, each content group of the plurality of topic groups containing only messages having content related to a topic of the content group; counting a number of messages in a content group to determine a popularity of a specific topic; determining a baseline computing resource allocation for the networked computing environment based upon a relationship between the social networking trend data over a plurality of time periods and historical computing resource data over the plurality of time periods stored in at least one computer storage device, the baseline computing resource allocation being a temporally segmented resource allocation plan; analyzing real-time social networking data against the social networking trend data to determine a change in the social networking trends based on a change in the popularity of a specific topic; determining a forecasted computing resource allocation for the networked computing environment based on an impact of the change in the social networking trends for the specific topic on hardware and software elements of the networked computing environment that are related to the specific topic; comparing the baseline computing resource allocation to the forecasted computing resource allocation to identify cloud-based hardware and software elements required to reach the forecasted computing resource allocation from the baseline computing resource allocation; and dynamically altering a computing resource allocation protocol to provision or de-provision the cloud-based hardware and software elements based on the comparing. 2. The computer-implemented method of claim 1 , comprising analyzing historical logs of computing resource utilization. 3. The computer-implemented method of claim 1 , the baseline computing resource allocation comprising a level of computing resources needed to process an expected level of traffic in the networked computing environment. 4. The computer-implemented method of claim 1 , the social network trend data being real-time data. 5. The computer-implemented method of claim 1 , the computing resource allocation protocol comprising a modification of the baseline computing resource allocation to meet the forecasted computing resource allocation. 6. The computer-implemented method of claim 1 , the analyzing comprising identifying a set of tags, which are related to topics of impact to the networked computing environment, in the social networking trend data and counting a number of the set of tags to determine a level of social networking activity, wherein the set of tags includes at least one hash tag. 7. The computer-implemented method of claim 1 , the networked computing environment comprising a cloud computing environment. 8. A system for allocating computing resources based on social networking trends in a networked computing environment, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and a processor coupled to the bus that when executing the instructions causes the system to: receive publically available topic-based social networking trend data that is external to the networked computing environment and corresponds to usage of a set of social networking websites that are unaffiliated with the networked computing environment; group messages in the publically available topic-based social networking trend data into a plurality of topic groups, each content group of the plurality of topic groups containing only messages having content related to a topic of the content group; count a number of messages in a content group to determine a popularity of a specific topic; determine a baseline computing resource allocation for the networked computing environment based upon a relationship between the social networking trend data over a plurality of time periods and historical computing resource data over the plurality of time periods stored in at least one computer storage device, the baseline computing resource allocation being a temporally segmented resource allocation plan; analyze real-time social networking data against the social networking trend data to determine a change in the social networking trends based on a change in the popularity of a specific topic; determine a forecasted computing resource allocation for the networked computing environment based on an impact of the change in the social networking trends for the specific topic on hardware and software elements of the networked computing environment that are related to the specific topic; compare the baseline computing resource allocation to the forecasted computing resource allocation to identify cloud-based hardware and software elements required to reach the forecasted computing resource allocation from the baseline computing resource allocation; and dynamically alter a computing resource allocation protocol to provision or de-provision the cloud-based hardware and software elements based on the comparison. 9. The system of claim 8 , the memory medium further comprising instructions for causing the system to analyze historical logs of computing resource utilization. 10. The system of claim 8 , the baseline computing resource allocation comprising a level of computing resources needed to process an expected level of traffic in the networked computing environment. 11. The system of claim 8 , the social network trend data being real-time data. 12. The system of claim 8 , the computing resource allocation protocol comprising a modification of the baseline computing resource allocation to meet the forecasted computing resource allocation. 13. The system of claim 8 , the memory medium further comprising instructions for causing the system to identify a set of tags, which are related to topics of impact to the networked computing environment, in the social networking trend data and to count a number of the set of tags to determine a level of social networking activity, wherein the set of tags includes at least one hash tag. 14. The system of claim 8 , the networked computing environment comprising a cloud computing environment. 15. A computer program product for allocating computing resources based on social networking trends in a networked computing environment, the computer program product comprising a computer readable storage device, and program instructions stored on the computer readable storage media, to: receive publically available topic-based social networking trend data that is external to the networked computing environment and corresponds to usage of a set of social networking websites that are unaffiliated with the networked computing environment; group messages in the publically available topic-based social networking trend data into a plurality of topic groups, each content group of the plurality of topic groups containing only messages having content related to a topic of the content group; count a number of messages in a content group to determine a popularity of a specific topic; determine a baseline computing resource allocation for the networked computing environment based upon a relationship between the soc
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