Article

SLA-based Optimization of Power and Migration Cost in Cloud Computing

Authors:

Mohammad Ghasemazar,

Massoud PedramAuthors Info & Claims

CCGRID '12: Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)

Pages 172 - 179

https://doi.org/10.1109/CCGrid.2012.112

Published: 13 May 2012 Publication History

Abstract

Cloud computing systems (or hosting datacenters) have attracted a lot of attention in recent years. Utility computing, reliable data storage, and infrastructure-independent computing are example applications of such systems. Electrical energy cost of a cloud computing system is a strong function of the consolidation and migration techniques used to assign incoming clients to existing servers. Moreover, each client typically has a service level agreement (SLA), which specifies constraints on performance and/or quality of service that it receives from the system. These constraints result in a basic trade-off between the total energy cost and client satisfaction in the system. In this paper, a resource allocation problem is considered that aims to minimize the total energy cost of cloud computing system while meeting the specified client-level SLAs in a probabilistic sense. The cloud computing system pays penalty for the percentage of a client's requests that do not meet a specified upper bound on their service time. An efficient heuristic algorithm based on convex optimization and dynamic programming is presented to solve the aforesaid resource allocation problem. Simulation results demonstrate the effectiveness of the proposed algorithm compared to previous work.

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SLA-based Optimization of Power and Migration Cost in Cloud Computing

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cover image ACM Conferences

CCGRID '12: Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)

May 2012

936 pages

ISBN:9780769546919

Sponsors

SIGARCH: ACM Special Interest Group on Computer Architecture

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IEEE Computer Society

United States

Publication History

Published: 13 May 2012

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Cited By

Hussain AAl-Turjman F(2022)Hybrid Genetic Algorithm for IOMT-Cloud Task SchedulingWireless Communications & Mobile Computing10.1155/2022/66042862022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/6604286
(2019)Executing time and cost-aware task scheduling in hybrid cloud using a modified DE algorithmInternational Journal of Computational Science and Engineering10.5555/3337494.333749618:3(217-226)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.5555/3337494.3337496
Olsson TFranke UDumas MPfahl DApel SRusso A(2019)Risks and assets: a qualitative study of a software ecosystem in the mining industryProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3340443(895-904)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3338906.3340443
Gawali MShinde S(2018)Task scheduling and resource allocation in cloud computing using a heuristic approachJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-018-0105-87:1(1-16)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1186/s13677-018-0105-8
Chen XTang JZhang Y(2017)Towards A Virtual Machine Migration Algorithm Based On Multi-Objective OptimizationInternational Journal of Mobile Computing and Multimedia Communications10.4018/IJMCMC.20170701068:3(79-89)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.4018/IJMCMC.2017070106
Mazumdar SPranzo M(2017)Power efficient server consolidation for Cloud data centerFuture Generation Computer Systems10.1016/j.future.2016.12.02270:C(4-16)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.future.2016.12.022
Momtazpour M(2017)Towards designing a green data center farm for Internet servicesThe Journal of Supercomputing10.1007/s11227-016-1852-273:4(1600-1628)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s11227-016-1852-2
Feng GBuyya R(2016)Maximum revenue-oriented resource allocation in cloudInternational Journal of Grid and Utility Computing10.1504/IJGUC.2016.0737727:1(12-21)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1504/IJGUC.2016.073772
Anan MAl-Fuqaha ANasser NMu TBustam H(2016)Empowering networking research and experimentation through Software-Defined NetworkingJournal of Network and Computer Applications10.1016/j.jnca.2016.05.00170:C(140-155)Online publication date: 1-Jul-2016
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(2016)Software consolidation as an efficient energy and cost saving solutionFuture Generation Computer Systems10.1016/j.future.2015.11.02758:C(1-12)Online publication date: 1-May-2016
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