Social objectives-based workload resolution in a cloud environment

Patent metadata

Field	Value
Publication number	US-10620997-B2
Application number	US-201816188401-A
Country	US
Kind code	B2
Filing date	Nov 13, 2018
Priority date	Aug 15, 2016
Publication date	Apr 14, 2020
Grant date	Apr 14, 2020

Abstract

A content of a social media data is analyzed. The social media data relates to a workload that is to be located on a node. A location corresponding to the social media data is computed. The social media data is regarded as originating from the location. A set of nodes is selected by computing a social distance objective function, the set of nodes includes the node. Each node in the set of nodes is located within a range of distances specified by the social distance objective function. A first subset of nodes is removed from the set of nodes, where the first subset of nodes fails to satisfy another objective function. In response to a second subset of nodes satisfying the social distance objective function and the other objective function, the node is selected from the second subset and the workload is deployed on the node.

First claim

What is claimed is:

1. A method comprising:
analyzing, using a processor and a memory, a content of a social media data, the social media data relating to a workload that is to be located on a node;
computing, using the processor and the memory, a location corresponding to the social media data, wherein the social media data is regarded as originating from the location;
selecting, using the processor and the memory, a set of nodes by computing a social distance objective function, the set of nodes including the node, and wherein each node in the set of nodes is located within a range of distances specified by the social distance objective function;
removing, using the processor and the memory, from the set of nodes a first subset of nodes, wherein the first subset of nodes fails to satisfy another objective function;
selecting, using the processor and the memory, responsive to a second subset of nodes satisfying the social distance objective function and the other objective function, the node from the second subset;
deploying, using the processor and the memory, the workload at the node;
replacing, responsive to a sentiment value of a sentiment expressed in the content being in an undesirable range, the node with a second node; and
migrating, as a part of the replacing, the workload from the node to the second node, wherein the social media data is related to a current interaction of users with the workload located at the node.

2. The method of claim 1 , further comprising:
performing a semantic analysis of the content to determine the sentiment value of the sentiment expressed in the content;
selecting a social semantic objective function responsive to the sentiment value being in the undesirable range; and
selecting the second node by computing the social semantic objective function, wherein the second node is located in a geographical region such that a configuration of the second node in the geographical region operates the second node to change the sentiment value from being in the undesirable range to a desirable range.

3. The method of claim 1 , wherein the social distance objective function minimizes the distance between a geographical location of the node and the computed location corresponding to the social media data.

4. The method of claim 1 , further comprising:
determining that the social media data comprises a plurality of contributions from a corresponding plurality of users;
determining a plurality of locations of origin corresponding to the plurality of contributions; and
applying a function to the plurality of locations to compute the location.

5. The method of claim 1 , wherein the social media data corresponds to an interaction with a second workload at a past time, the second workload having a similarity with the workload.

6. The method of claim 1 , wherein the social media data corresponds to an interaction with the workload at a past time.

7. The method of claim 1 , further comprising:
determining that the content is a multimedia content; performing, a multimedia analysis of the multimedia content; and
deducing, from the multimedia analysis, a geographical location from where the social media data was contributed.

8. The method of claim 7 , wherein the deducing is performed without using any location data associated with the social media data.

9. The method of claim 1 , further comprising:
determining that the content is a textual content; performing, using Natural Language Processing (NLP), a textual analysis of the textual content; and
deducing, from the textual analysis, a geographical location from where the social media data was contributed.

10. The method of claim 9 , wherein the deducing is performed without using any location data associated with the social media data.

11. The method of claim 1 , wherein the node is a part of a geographically dispersed cloud computing environment.

12. A computer usable program product comprising one or more computer-readable medium, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to analyze a content of a social media data, the social media data relating to a workload that is to be located on a node;
program instructions to compute a location corresponding to the social media data, wherein the social media data is regarded as originating from the location;
program instructions to select a set of nodes by computing a social distance objective function, the set of nodes including the node, and wherein each node in the set of nodes is located within a range of distances specified by the social distance objective function;
program instructions to remove from the set of nodes a first subset of nodes, wherein the first subset of nodes fails to satisfy another objective function;
program instructions to select, responsive to a second subset of nodes satisfying the social distance objective function and the other objective function, the node from the second subset;
program instructions to deploy the workload at the node;
program instructions to replace, responsive to a sentiment value of a sentiment expressed in the content being in an undesirable range, the node with a second node; and
program instructions to migrate, as a part of the program instructions to replace, the workload from the node to the second node, wherein the social media data is related to a current interaction of users with the workload located at the node.

13. The computer usable program product of claim 12 , further comprising:
program instructions to perform a semantic analysis of the content to determine the sentiment value of the sentiment expressed in the content;
program instructions to select a social semantic objective function responsive to the sentiment value being in the undesirable range; and
program instructions to select the second node by computing the social semantic objective function, wherein the second node is located in a geographical region such that a configuration of the second node in the geographical region operates the second node to change the sentiment value from being in the undesirable range to a desirable range.

14. The computer usable program product of claim 12 , wherein the social distance objective function minimizes the distance between a geographical location of the node and the computed location corresponding to the social media data.

15. The computer usable program product of claim 12 , further comprising:
program instructions to determine that the social media data comprises a plurality of contributions from a corresponding plurality of users;
program instructions to determine a plurality of locations of origin corresponding to the plurality of contributions; and
program instructions to apply a function to the plurality of locations to compute the location.

16. The computer usable program product of claim 12 , wherein the computer usable code is stored in a computer readable storage device in a data processing system, and wherein the computer usable code is transferred over a network from a remote data processing system.

17. The computer usable program product of claim 12 , wherein the computer usable code is stored in a computer readable storage device in a server data processing system, and wherein the computer usable code is downloaded over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system.

18. A computer system comprising one or more processors, one or more

Assignees

• IBM

Inventors

• Baughman Aaron K
• Cope John S
• Welcks Michelle
• O'Connell Brian M

Classifications

• G06F9/5077

  Logical partitioning of resources; Management or configuration of virtualized resources (specific details on emulation or internal functioning of virtual machines G06F9/455) · CPC title

• G06F9/4875

  with migration policy, e.g. auction, contract negotiation · CPC title

• G06F9/5011

  the resources being hardware resources other than CPUs, Servers and Terminals · CPC title

• G06F9/5022

  Mechanisms to release resources · CPC title

• G06F9/5016

  the resource being the memory · CPC title