Many-Objective Cloud Task Scheduling

Task scheduling problem refers to how to reasonably arrange many tasks provided by users in virtual machines, which is very important in the cloud computing. And the quality of the scheduling performance directly affects the customer satisfaction and the provider benefits. In order to describe the t...

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Vydáno v:IEEE access Ročník 8; s. 79079 - 79088
Hlavní autoři: Geng, Shaojin, Wu, Di, Wang, Penghong, Cai, Xingjuan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Cloud computing
Customer satisfaction
hybrid-angle strategy
Job shop scheduling
many-objective algorithm
Multiple objective analysis
Optimization
Processor scheduling
Resource utilization
Scheduling
Task analysis
Task scheduling
Virtual environments
Virtual machining
ISSN:2169-3536, 2169-3536
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Shrnutí:Task scheduling problem refers to how to reasonably arrange many tasks provided by users in virtual machines, which is very important in the cloud computing. And the quality of the scheduling performance directly affects the customer satisfaction and the provider benefits. In order to describe the task scheduling problem of cloud computing more precisely and improve the scheduling performance. This paper establishes many-objective cloud model, including four objectives: minimizing time, minimizing costs, maximizing resource utilization, and balancing load. At the same time, a many-objective optimization algorithm based on hybrid angles (MaOEA-HA) is proposed to solve this model. Hybrid angle strategy is designed to optimize the algorithm better, which combines two angle strategies: individual-to-individual angle and individual-to-reference point angle. One by one elimination strategy was introduced to remain individuals with better performance. By comparing with five other advanced many-objective optimization algorithms, MaOEA-HA shows the best performance on the DTLZ test suite. Moreover, different algorithms are applied to solve the cloud task scheduling problem, and MaOEA-HA algorithm achieves best results.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2990500