A Survey of PSO-Based Scheduling Algorithms in Cloud Computing

Cloud computing provides effective mechanisms for distributing the computing tasks to the virtual resources. To provide cost-effective executions and achieve objectives such as load balancing, availability and reliability in the cloud environment, appropriate task and workflow scheduling solutions a...

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Veröffentlicht in:	Journal of network and systems management Jg. 25; H. 1; S. 122 - 158
Hauptverfasser:	Masdari, Mohammad, Salehi, Farbod, Jalali, Marzie, Bidaki, Moazam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.01.2017 Springer Nature B.V
Schlagworte:	Algorithms Classification Cloud computing Communications Engineering Computer Communication Networks Computer engineering Computer Science Computer Systems Organization and Communication Networks Cost analysis Function words Heuristic Information Systems and Communication Service Load Networks Objectives Operations Research/Decision Theory Optimization Optimization techniques Population Property Reliability Scheduling Software services Swarm intelligence Systems management Task scheduling Tasks Velocity Workflow Task Workflow SLA Makespan Meta-heuristic Load balancing PSO Cost
ISSN:	1064-7570, 1573-7705
Online-Zugang:	Volltext
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Abstract	Cloud computing provides effective mechanisms for distributing the computing tasks to the virtual resources. To provide cost-effective executions and achieve objectives such as load balancing, availability and reliability in the cloud environment, appropriate task and workflow scheduling solutions are needed. Various metaheuristic algorithms are applied to deal with the problem of scheduling, which is an NP-hard problem. This paper presents an in-depth analysis of the Particle Swarm Optimization (PSO)-based task and workflow scheduling schemes proposed for the cloud environment in the literature. Moreover, it provides a classification of the proposed scheduling schemes based on the type of the PSO algorithms which have been applied in these schemes and illuminates their objectives, properties and limitations. Finally, the critical future research directions are outlined.
AbstractList	Cloud computing provides effective mechanisms for distributing the computing tasks to the virtual resources. To provide cost-effective executions and achieve objectives such as load balancing, availability and reliability in the cloud environment, appropriate task and workflow scheduling solutions are needed. Various metaheuristic algorithms are applied to deal with the problem of scheduling, which is an NP-hard problem. This paper presents an in-depth analysis of the Particle Swarm Optimization (PSO)-based task and workflow scheduling schemes proposed for the cloud environment in the literature. Moreover, it provides a classification of the proposed scheduling schemes based on the type of the PSO algorithms which have been applied in these schemes and illuminates their objectives, properties and limitations. Finally, the critical future research directions are outlined.
Author	Salehi, Farbod Jalali, Marzie Masdari, Mohammad Bidaki, Moazam
Author_xml	– sequence: 1 givenname: Mohammad surname: Masdari fullname: Masdari, Mohammad email: M.Masdari@Iaurmia.ac.ir organization: Department of Computer Engineering, Urmia Branch, Islamic Azad University – sequence: 2 givenname: Farbod surname: Salehi fullname: Salehi, Farbod organization: Department of Computer Engineering, Urmia Branch, Islamic Azad University – sequence: 3 givenname: Marzie surname: Jalali fullname: Jalali, Marzie organization: Department of Computer Engineering, Urmia Branch, Islamic Azad University – sequence: 4 givenname: Moazam surname: Bidaki fullname: Bidaki, Moazam organization: Department of Computer Engineering, Neyshabur Branch, Islamic Azad University
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SubjectTerms	Algorithms Classification Cloud computing Communications Engineering Computer Communication Networks Computer engineering Computer Science Computer Systems Organization and Communication Networks Cost analysis Function words Heuristic Information Systems and Communication Service Load Networks Objectives Operations Research/Decision Theory Optimization Optimization techniques Population Property Reliability Scheduling Software services Swarm intelligence Systems management Task scheduling Tasks Velocity Workflow
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Title	A Survey of PSO-Based Scheduling Algorithms in Cloud Computing
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