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CloudGenius: A Hybrid Decision Support Method for Automating the Migration of Web Application Clusters to Public Clouds
| Citations: | 3 - 0 self |
BibTeX
@MISC{Menzel_cloudgenius:a,
author = {Michael Menzel and Rajiv Ranjan and Lizhe Wang and Senior Member and Samee U. Khan and Senior Member and Jinjun Chen and Senior Member},
title = {CloudGenius: A Hybrid Decision Support Method for Automating the Migration of Web Application Clusters to Public Clouds},
year = {}
}
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Abstract
Abstract—With the increase in cloud service providers, and the increasing number of compute services offered, a migration of information systems to the cloud demands selecting the best mix of compute services and VM (Virtual Machine) images from an abundance of possibilities. Therefore, a migration process for web applications has to automate evaluation and, in doing so, ensure that Quality of Service (QoS) requirements are met, while satisfying conflicting selection criteria like throughput and cost. When selecting compute services for multiple connected software components, web application engineers must consider heterogeneous sets of criteria and complex dependencies across multiple layers, which is impossible to resolve manually. The previously proposed CloudGenius framework has proven its capability to support migrations of single-component web applications. In this paper, we expand on the additional complexity of facilitating migration support for multi-component web applications. In particular, we present an evolutionary migration process for web application clusters distributed over multiple locations, and clearly identify the most important criteria relevant to the selection problem. Moreover, we present a multi-criteria-based selection algorithm based on Analytic Hierarchy Process (AHP). Because the solution space grows exponentially, we developed a Genetic Algorithm (GA)-based approach to cope with computational complexities in a growing cloud market. Furthermore, a use case example proofs CloudGenius ’ applicability. To conduct experiments, we implemented CumulusGenius,
Keyphrases
web application cluster compute service public cloud hybrid decision support method virtual machine selection problem cloud service provider important criterion multi-criteria-based selection algorithm analytic hierarchy process additional complexity multiple location multi-component web application cloudgenius framework complex dependency web application genetic algorithm heterogeneous set single-component web application web application engineer migration support cloud market information system evolutionary migration process multiple layer computational complexity solution space software component selection criterion migration process
