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research-article

CloudGenius: A Hybrid Decision Support Method for Automating the Migration of Web Application Clusters to Public Clouds

Authors:

Michael Menzel,

Jinjun ChenAuthors Info & Claims

IEEE Transactions on Computers, Volume 64, Issue 5

Pages 1336 - 1348

https://doi.org/10.1109/TC.2014.2317188

Published: 01 May 2015 Publication History

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 virtual machine (VM ) 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, a prototype of the selection algorithm and the GA deployable on hadoop clusters. Experiments with CumulusGenius give insights on time complexities and the quality of the GA.

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Cited By

Shi TMa HChen GHartmann S(2022)Cost-Effective Web Application Replication and Deployment in Multi-Cloud EnvironmentIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.313388433:8(1982-1995)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1109/TPDS.2021.3133884
Belusso CSawicki SBasto-Fernandes VFrantz RRoos-Frantz F(2022)Selecting services in the cloud: a decision support methodology focused on infrastructure-as-a-service contextThe Journal of Supercomputing10.1007/s11227-021-04248-878:6(7825-7860)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s11227-021-04248-8
Tomar AKumar RGupta I(2022)Decision making for cloud service selection: a novel and hybrid MCDM approachCluster Computing10.1007/s10586-022-03793-y26:6(3869-3887)Online publication date: 31-Oct-2022
https://dl.acm.org/doi/10.1007/s10586-022-03793-y
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cover image IEEE Transactions on Computers

IEEE Transactions on Computers Volume 64, Issue 5

May 2015

289 pages

ISSN:0018-9340

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Copyright © 2014.

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IEEE Computer Society

United States

Publication History

Published: 01 May 2015

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Shi TMa HChen GHartmann S(2022)Cost-Effective Web Application Replication and Deployment in Multi-Cloud EnvironmentIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.313388433:8(1982-1995)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1109/TPDS.2021.3133884
Belusso CSawicki SBasto-Fernandes VFrantz RRoos-Frantz F(2022)Selecting services in the cloud: a decision support methodology focused on infrastructure-as-a-service contextThe Journal of Supercomputing10.1007/s11227-021-04248-878:6(7825-7860)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s11227-021-04248-8
Tomar AKumar RGupta I(2022)Decision making for cloud service selection: a novel and hybrid MCDM approachCluster Computing10.1007/s10586-022-03793-y26:6(3869-3887)Online publication date: 31-Oct-2022
https://dl.acm.org/doi/10.1007/s10586-022-03793-y
Sivagami RKrishankumar RSangeetha VRavichandran KKar SGandomi A(2021)Assessment of cloud vendors using interval‐valued probabilistic linguistic information and unknown weightsInternational Journal of Intelligent Systems10.1002/int.2243936:8(3813-3851)Online publication date: 30-Jun-2021
https://dl.acm.org/doi/10.1002/int.22439
Krishankumar RRavichandran KTyagi S(2020)Solving cloud vendor selection problem using intuitionistic fuzzy decision frameworkNeural Computing and Applications10.1007/s00521-018-3648-132:2(589-602)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1007/s00521-018-3648-1
Brogi ACorradini ASoldani J(2019)Estimating costs of multi-component enterprise applicationsFormal Aspects of Computing10.1007/s00165-019-00491-231:4(421-451)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s00165-019-00491-2
Balobaid ADebnath D(2018)Cloud Migration Tools: Overview and ComparisonServices – SERVICES 201810.1007/978-3-319-94472-2_7(93-106)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-94472-2_7
Weerasiri DBarukh MBenatallah BSheng QRanjan R(2017)A Taxonomy and Survey of Cloud Resource Orchestration TechniquesACM Computing Surveys10.1145/305417750:2(1-41)Online publication date: 10-May-2017
https://dl.acm.org/doi/10.1145/3054177
Tsakalozos KVerroios VRoussopoulos MDelis A(2017)Live VM Migration Under Time-Constraints in Share-Nothing IaaS-CloudsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2017.265857228:8(2285-2298)Online publication date: 13-Jul-2017
https://dl.acm.org/doi/10.1109/TPDS.2017.2658572

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