A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems
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- 作者：Saima Gulzar Ahmada ; saimagulzarahmad@siswa.um.edu.my" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Chee Sun Liewa ; csliew@um.edu.my" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Ehsan Ullah Munirb ; ehsanmunir@comsats.edu.pk" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Tan Fong Anga ; angtf@um.edu.my" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Samee U. Khanc ; samee.khan@ndsu.edu" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Workflow ; Genetic algorithm ; Heuristic ; Directed Acyclic Graphs
- 刊名：Journal of Parallel and Distributed Computing
- 出版年：2016
- 出版时间：January 2016
- 年：2016
- 卷：87
- 期：Complete
- 页码：80-90
- 全文大小：1464 K
文摘
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Proposed HGA (hybrid GA) to schedule workflow in heterogeneous environment.
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Simulation results are presented with synthesized and real-world workflows.
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HGA identifies lesser length of the workflows.
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HGA also improves load balancing.
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Significant improvement in schedule lengths as compared to existing work.