Date of Award

2015

Publisher

North Dakota State University

Document Type

Thesis

Degree Awarded

Master of Science (MS)

Program

Computer Science

Department

Computer Science

College

Engineering

Faculty Advisor

Ludwig, Simone

Description

Serving the needs efficiently for a wide gamut of cloud users is a challenge. One way to address this challenge is to decompose SaaS (Software as a Service) into application components and then consider them as loosely coupled processes that achieve higher functionality. Optimization occurs in efficiently pairing virtual machines to application components in order to lower operating costs for cloud service providers and to lower subscription costs for customers. This thesis explores utilizing an immune network algorithm that mimics antibody activation and antigen and antibody suppression for resource optimization. Experiments are conducted with a series of SaaS configurations, application components placed with virtual machines. Results generated by the proposed algorithm are compared with a previously proposed grouping genetic algorithm. This data reveals that the immune network algorithm outperforms the grouping genetic algorithm in time taken to calculate a resource distribution strategy.

Rights

NDSU Policy 190.6.2

Rights Link

https://www.ndsu.edu/fileadmin/policy/190.pdf

Handle Identifier

https://hdl.handle.net/10365/27709

Download

Share

COinS