Workflow scheduling optimization method based on multi-decoding genetic algorithm in cloud computing environment

Abstract

The invention discloses a cloud workflow scheduling optimization method based on a multi-decoding genetic algorithm in a cloud computing environment. The cloud workflow scheduling optimization methodcomprises the following steps: acquiring information required by scheduling; calculating a task hierarchy value; initializing a contemporary population; carrying out evolution; forming a new population by adopting crossover operation and carrying out mutation operation; carrying out individual decoding and updating based on serial individual decoding of an insertion mode, heuristic decoding of theearliest task completion time and heuristic decoding of dynamic key task priority scheduling; improving the new population by adopting FBI & D and LDI methods, forming a next-generation population bythe contemporary population and the new population, and enabling the next-generation population to be a contemporary population until an evolution termination condition is met; and outputting a scheduling scheme corresponding to the best individual in the contemporary population. Compared with a single decoding strategy, the method has higher efficiency and optimization capability, and the solving quality can be improved.

Description

technical field [0001] The present invention relates to the fields of computer technology, information technology and system engineering, in particular to a workflow scheduling optimization method, more specifically, to a workflow scheduling optimization method based on a multi-decoding genetic algorithm in a cloud computing environment. Background technique [0002] Workflow under the cloud computing environment, referred to as "cloud workflow", is the integration of cloud computing and workflow-related technologies. Management, supply chain management and health care and other fields have broad application prospects. In cloud workflow, there are timing constraints between tasks, and virtual machines are usually used as the smallest allocation unit of computing resources to receive and process these tasks during execution. Cloud workflow scheduling refers to how to assign tasks in the cloud workflow to appropriate virtual machines under the constraints of task timing and u...

AI Technical Summary

Problems solved by technology

[0011] In order to overcome the quality of the heuristic method solution is usually not very high and depends on the type of workflow, combined with the heuristic semi-intelligent computing method, the intelligent computing method based on hierarchical coding, the incompleteness of the coding search space, and the global-based one-way The single decoding intelligent computing method has insufficient search efficiency, etc. The present invention provides a workflow scheduling optimization method based on a multi-decoding genetic algorithm in a cloud computing environment, which effectively improves the efficiency and quality of the solution

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