Workflow scheduling method for multi-target particle swarm optimization based on real-time state monitoring
The invention discloses a workflow scheduling method for multi-target particle swarm optimization based on real-time state monitoring and relates to the field of cloud computing workflow scheduling. According to the method, first, workflow pre-scheduling is performed through a BHEFT algorithm, and t...
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| creator | BAO XIAO'AN CAO YUNDI ZHANG NA |
| description | The invention discloses a workflow scheduling method for multi-target particle swarm optimization based on real-time state monitoring and relates to the field of cloud computing workflow scheduling. According to the method, first, workflow pre-scheduling is performed through a BHEFT algorithm, and the feasibility of the algorithm is improved; and a Pareto variance is introduced to perform real-time monitoring on an evolution state, wherein when the evolution state is in diversification, an external elite swarm self-optimization strategy is adopted to improve local search capability of the algorithm, and when the evolution state is in stagnation, an escape strategy is adopted, so that workflow scheduling solution spaces are diversified. In this way, development and exploitation of the algorithm in the evolution process are effectively balanced, and the convergence of workflow scheduling solutions and the diversity of scheduling solution space distribution are realized.
本发明公开了种基于实时状态监控的多目标粒子群优化的工作流调度方法，涉及云计算工作流 |
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本发明公开了种基于实时状态监控的多目标粒子群优化的工作流调度方法，涉及云计算工作流</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Workflow scheduling method for multi-target particle swarm optimization based on real-time state monitoring |
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