SYSTEMS AND METHODS FOR ASSESSING HYBRIDIZATION OF CLOUD COMPUTING SERVICES BASED ON DATA MINING OF HISTORICAL DECISIONS

• US 20150134424A1
• Filed: 11/14/2013
• Published: 05/14/2015
• Est. Priority Date: 11/14/2013
• Status: Abandoned Application

• Current Assignee: VMware, Inc. (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Matzlavi, Dani, Etz-Hadar, Meidad
• Application Number:
  US14/080,661
• Publication Number:
  US 20150134424A1
• Time in Patent Office: Days
• US Class Current: 705/7.36
• CPC Class Codes: G06F 9/5072 Grid computing
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: H04L 41/14 Network analysis or design
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network

Abstract

Computational methods and systems that aid an enterprise in deciding whether to execute an application entirely within a private cloud or a hybrid combination of the private cloud and public cloud services offered by a public cloud service provider are described. The methods and system receive a set of quantitative parameters associated with running an application using computational services provided by a public cloud service provider and a set of organizational parameters associated with an enterprise. The quantitative and organizational parameters are normalized and input to a decision model that generates a recommendation that indicates exclusive use of a private cloud or a hybrid private cloud and public cloud to execute the application.

Claims

1. A system for aiding an enterprise in deciding to execute an application in a private cloud or in a hybrid private cloud and public cloud, the system comprising:

one or more processors;

one or more data-storage devices; and

a routine stored in the data-storage devices that when executed using the one or more processors

receives a set of quantitative parameters associated with running the application using computational services provided by a public cloud service provider;

receives a set of organizational parameters associated with the enterprise;

normalizes the quantitative and organizational parameters;

inputs the normalized quantitative and organization parameters to a decision model that generates a recommendation that indicates exclusive use of a private cloud or a hybrid private cloud and public cloud to execute the application; and

stores the recommendation on the one or more data-storage devices.

2. The system of claim 1, wherein the set of quantitative parameters comprises one or more of cost of service, computing resources, number of dependencies, and performance service level agreement.

3. The system of claim 1, wherein the set of organization parameters comprises one or more of criticality, regulations, and the enterprises organization approach.

4. The system of claim 1, wherein the decision model comprises a decision tree generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

5. The system of claim 1, wherein the decision model comprises a neural network generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

6. The system of claim 1, wherein the recommendation output from the decision model comprises one of a recommendation to hybridize with an associated probability, a recommendation not hybridize, and instructions not to hybridize based regulations that prohibit the enterprise from hybridizing the application.

7. A method stored in one or more data-storage devices and executed using one or more processors that aids an enterprise in deciding to execute an application in a private cloud or in a hybrid private cloud and public cloud, the method comprising:

receiving a set of quantitative parameters associated with running an application using computational services provided by a public cloud service provider;

receiving a set of organizational parameters associated with an enterprise;

normalizing the quantitative and organizational parameters;

inputting the normalized quantitative and organization parameters to a decision model that generates a recommendation that indicates exclusive use of a private cloud or a hybrid private cloud and public cloud to execute the application; and

storing the recommendation on the one or more data-storage devices.

8. The method of claim 7, wherein the set of quantitative parameters comprises one or more of cost of service, computing resources, number of dependencies, and performance service level agreement.

9. The method of claim 7, wherein the set of organization parameters comprises one or more of criticality, regulations, and the enterprises organization approach.

10. The method of claim 7, wherein the decision model comprises a decision tree generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

11. The method of claim 7, wherein the decision model comprises a neural network generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

12. The method of claim 7, wherein the recommendation output from the decision model comprises one of a recommendation to hybridize with an associated probability, a recommendation not hybridize, and instructions not to hybridize based regulations that prohibit the enterprise from hybridizing the application.

16. The method of claim 7, wherein the decision model comprises a decision tree generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

13. A computer-readable medium encoded with machine-readable instructions that implement a method carried out by one or more processors of a computer system to perform the operations of

receiving a set of quantitative parameters associated with running an application using computational services provided by a public cloud service provider;

receiving a set of organizational parameters associated with an enterprise;

normalizing the quantitative and organizational parameters;

inputting the normalized quantitative and organization parameters to a decision model that generates a recommendation that indicates exclusive use of a private cloud or a hybrid private cloud and public cloud to execute the application; and

storing the recommendation on the one or more data-storage devices.

14. The medium of claim 13, wherein the set of quantitative parameters comprises one or more of cost of service, computing resources, number of dependencies, and performance service level agreement.

15. The medium of claim 13, wherein the set of organization parameters comprises one or more of criticality, regulations, and the enterprises organization approach.

17. The medium of claim 13, wherein the decision model comprises a neural network generated from a training set of services, quantitative and organization parameters, and hybridization goals, each goal indicating a decision to hybridize or not to hybridize based on a service and corresponding quantitative and organization parameters.

18. The medium of claim 13, wherein the recommendation output from the decision model comprises one of a recommendation to hybridize with an associated probability, a recommendation not hybridize, and instructions not to hybridize based regulations that prohibit the enterprise from hybridizing the application.