An Enhanced PSO Algorithm for Scheduling Workflow Tasks in Cloud Computing

This paper proposes an enhanced Particle Swarm Optimization (PSO) algorithm in order to deal with the issue that the time and cost of the PSO algorithm is quite high when scheduling workflow tasks in a cloud computing environment. To reduce particle dimensions and ensure initial particle quality, in...

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Veröffentlicht in:Electronics (Basel) Jg. 12; H. 12; S. 2580
Hauptverfasser: Anbarkhan, Samar Hussni, Rakrouki, Mohamed Ali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.06.2023
Schlagworte:
Algorithms
Bandwidths
Cloud computing
Communication
Data transmission
Distributed processing
Mathematical optimization
Methods
Mutation
Optimization
Particle swarm optimization
Quality of service
Scheduling
Scheduling (Management)
Task scheduling
User needs
Workflow
Saudi Arabia
ISSN:2079-9292, 2079-9292
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Zusammenfassung:This paper proposes an enhanced Particle Swarm Optimization (PSO) algorithm in order to deal with the issue that the time and cost of the PSO algorithm is quite high when scheduling workflow tasks in a cloud computing environment. To reduce particle dimensions and ensure initial particle quality, intensive tasks are combined when scheduling workflow tasks. Next, the particle initialization is optimized to ensure better initial particle quality and reduced search space. Then, a suitable self-adaptive function is integrated to determine the best direction of the particles. The experiments show that the proposed enhanced PSO algorithm has better convergence speed and better performance in the execution of workflow tasks.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics12122580