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Novel algorithms and equivalence optimisation for resource allocation in cloud computing

Authors:

Huiqiong LianAuthors Info & Claims

International Journal of Web and Grid Services, Volume 11, Issue 2

Pages 193 - 210

https://doi.org/10.1504/IJWGS.2015.068899

Published: 01 April 2015 Publication History

Abstract

In this paper, we model the optimisation of the resource allocation in cloud computing as a constraint satisfaction problem considering three types of resources CPU, RAM and bandwidth and design a Choco-Based algorithm CB for VM resource allocation in virtualised cloud data centres. We also propose an Improved First-Fit Decreasing Algorithm IFFD and an Improved Best-Fit Decreasing Algorithm IBFD and conduct performance evaluation experiments using Choco. The experimental results show that CB has better results, whereas its solution time is longer than IFFD and IBFD in resource allocation. Moreover, to reduce the complexity of solving the problem of CSP-based resource allocation, we propose an equivalence optimisation which can greatly reduce the search space for resource allocation by making tree pruning with resource equivalence. Then, a resource allocation algorithm based on Equivalent Optimisation EO is designed. Experimental results also show that compared with CB, EO greatly reduces the time of allocating resource of cloud computing.

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Cited By

Talaat FAli HSaraya MSaleh A(2022)Effective scheduling algorithm for load balancing in fog environment using CNN and MPSOKnowledge and Information Systems10.1007/s10115-021-01649-264:3(773-797)Online publication date: 1-Mar-2022
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Miri MDowlatshahi MHashemi ARafsanjani MGupta BAlhalabi W(2022)Ensemble feature selection for multi‐label text classificationInternational Journal of Intelligent Systems10.1002/int.2304437:12(11319-11341)Online publication date: 29-Dec-2022
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Novel algorithms and equivalence optimisation for resource allocation in cloud computing
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Published In

cover image International Journal of Web and Grid Services

International Journal of Web and Grid Services Volume 11, Issue 2

April 2015

103 pages

ISSN:1741-1106

EISSN:1741-1114

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Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 April 2015

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Cited By

Talaat FAli HSaraya MSaleh A(2022)Effective scheduling algorithm for load balancing in fog environment using CNN and MPSOKnowledge and Information Systems10.1007/s10115-021-01649-264:3(773-797)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s10115-021-01649-2
Miri MDowlatshahi MHashemi ARafsanjani MGupta BAlhalabi W(2022)Ensemble feature selection for multi‐label text classificationInternational Journal of Intelligent Systems10.1002/int.2304437:12(11319-11341)Online publication date: 29-Dec-2022
https://dl.acm.org/doi/10.1002/int.23044
Riyahi MRafsanjani MGupta BAlhalabi W(2022)Multiobjective whale optimization algorithm‐based feature selection for intelligent systemsInternational Journal of Intelligent Systems10.1002/int.2297937:11(9037-9054)Online publication date: 26-Sep-2022
https://dl.acm.org/doi/10.1002/int.22979
Azizi SZandsalimi MLi D(2020)An energy-efficient algorithm for virtual machine placement optimization in cloud data centersCluster Computing10.1007/s10586-020-03096-023:4(3421-3434)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s10586-020-03096-0
Liu LQi DZhou NWu Y(2018)A Task Scheduling Algorithm Based on Classification Mining in Fog Computing EnvironmentWireless Communications & Mobile Computing10.1155/2018/21023482018Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1155/2018/2102348
Aslanpour MDashti SGhobaei-Arani MRahmanian A(2018)Resource provisioning for cloud applicationsThe Journal of Supercomputing10.1007/s11227-017-2156-x74:12(6470-6501)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11227-017-2156-x
Liu BLi PLin WShu NLi YChang V(2018)A new container scheduling algorithm based on multi-objective optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3403-722:23(7741-7752)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s00500-018-3403-7
Lin WXu SHe LLi J(2017)Multi-resource scheduling and power simulation for cloud computingInformation Sciences: an International Journal10.1016/j.ins.2017.02.054397:C(168-186)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1016/j.ins.2017.02.054
Wu WLin WPeng Z(2017)An intelligent power consumption model for virtual machines under CPU-intensive workload in cloud environmentSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2154-621:19(5755-5764)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1007/s00500-016-2154-6
Lin WXu SLi JXu LPeng Z(2017)Design and theoretical analysis of virtual machine placement algorithm based on peak workload characteristicsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1862-721:5(1301-1314)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s00500-015-1862-7
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