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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Vydáno v:Electronics (Basel) Ročník 12; číslo 12; s. 2580
Hlavní autoři: Anbarkhan, Samar Hussni, Rakrouki, Mohamed Ali
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.06.2023
Témata:
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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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics12122580