Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing
For the issues that the existing task scheduling scheme based on intelligent algorithms can’t obtain the optimal solution in cloud computing and inspired by nature symbiosis,a new task scheduling scheme based on improved particle swarm optimization(PSO)with biological symbiosis mechanism(SM)was prop...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2016-09-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016241/ |
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| author | Linjie WANG |
| author_facet | Linjie WANG |
| author_sort | Linjie WANG |
| collection | DOAJ |
| description | For the issues that the existing task scheduling scheme based on intelligent algorithms can’t obtain the optimal solution in cloud computing and inspired by nature symbiosis,a new task scheduling scheme based on improved particle swarm optimization(PSO)with biological symbiosis mechanism(SM)was proposed.Firstly,the particles in PSO were divided into two populations,and the optimization process were performed alone.Then,after each execution of the k iteration of PSO,the individual in the two populations performed the mutualism and parasitism operation.The search process was optimized by mutualism operation to through the optimal solution region,which could enhance the search ability.The parasitism operation was used to avoid premature convergence by eliminating the poor and introducing the optimal solution.Finally,the optimal solution of the task scheduling was obtained.Simulation results show that the optimal scheduling scheme can obtain the minimum task completion time and response time. |
| format | Article |
| id | doaj-art-53e3095a140146e1b8afb6e6e9e4be4e |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2016-09-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-53e3095a140146e1b8afb6e6e9e4be4e2025-01-15T03:14:08ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012016-09-013211311959606723Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computingLinjie WANGFor the issues that the existing task scheduling scheme based on intelligent algorithms can’t obtain the optimal solution in cloud computing and inspired by nature symbiosis,a new task scheduling scheme based on improved particle swarm optimization(PSO)with biological symbiosis mechanism(SM)was proposed.Firstly,the particles in PSO were divided into two populations,and the optimization process were performed alone.Then,after each execution of the k iteration of PSO,the individual in the two populations performed the mutualism and parasitism operation.The search process was optimized by mutualism operation to through the optimal solution region,which could enhance the search ability.The parasitism operation was used to avoid premature convergence by eliminating the poor and introducing the optimal solution.Finally,the optimal solution of the task scheduling was obtained.Simulation results show that the optimal scheduling scheme can obtain the minimum task completion time and response time.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016241/cloudcomputingtaskschedulingbiologicalsymbiosismechanismparticleswarmoptimizationglobalsearchingcapability |
| spellingShingle | Linjie WANG Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing Dianxin kexue cloudcomputing taskscheduling biologicalsymbiosismechanism particleswarmoptimization globalsearchingcapability |
| title | Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| title_full | Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| title_fullStr | Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| title_full_unstemmed | Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| title_short | Task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| title_sort | task scheduling scheme based on improved particle swarm optimization with biological symbiosis mechanism in cloud computing |
| topic | cloudcomputing taskscheduling biologicalsymbiosismechanism particleswarmoptimization globalsearchingcapability |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016241/ |
| work_keys_str_mv | AT linjiewang taskschedulingschemebasedonimprovedparticleswarmoptimizationwithbiologicalsymbiosismechanismincloudcomputing |