CDOXplorer : simulation-based genetic optimization of software deployment and reconfiguration in the cloud

Frey, Sören, Fittkau, Florian and Hasselbring, Wilhelm (2018) CDOXplorer : simulation-based genetic optimization of software deployment and reconfiguration in the cloud Technical Reports of the Department of Computer Science at Kiel University, TR_1807 . Kiel University Library, Kiel.

[img]
Preview
Text
tr-1807.pdf - Published Version

Download (1954Kb) | Preview

Abstract

Migrating existing enterprise software to cloud platforms involves the comparison of various cloud deployment options (CDOs). A CDO comprises a combination of a specific cloud environment, deployment architecture, and runtime reconfiguration rules for dynamic resource scaling. Our simulator CDOSim can evaluate CDOs, e.g., regarding response times and costs. However, the design space to be searched for well-suited solutions is very large. In this paper, we approach this optimization problem with the novel genetic algorithm CDOXplorer. It uses techniques of the search-based software engineering field and simulations with CDOSim to assess the fitness of CDOs. An experimental evaluation that employs, among others, the cloud environments Amazon EC2 and Microsoft Windows Azure, shows that CDOXplorer can find solutions that surpass those of other state-of-the-art techniques by up to 60\%. Our experiment code and data and an implementation of CDOXplorer are available as open source software.

Document Type: Report (Research Report)
Keywords: cloud
Research affiliation: Kiel University > Software Engineering
ISSN: 2192-6247
Date Deposited: 26 Sep 2018 07:17
Last Modified: 26 Sep 2018 07:17
URI: http://eprints.uni-kiel.de/id/eprint/44386

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...