Workflow optimization method based on partial order adaptive genetic algorithm in cloud computing environment

Abstract

The invention discloses a workflow optimization method based on a partial order adaptive genetic algorithm in a cloud computing environment. The workflow optimization method comprises the following steps: acquiring information required for executing optimization; calculating a hierarchical value of the task; initializing a contemporary population; decoding the improved contemporary population andcalculating a fitness value; performing crossover mutation operation on the contemporary population to form a new population; forming a new contemporary population by the contemporary population and the new population; and outputting an execution optimization result until a termination condition is met. According to the workflow optimization method, methods and strategies of initial individual generation based on hierarchy and benefit ratio, adaptive genetic operation, topological sorting, non-decreasing partial order coding, serial individual decoding based on an insertion mode, forward and backward individual decoding improvement and the like are adopted; integrated collaborative optimization of resource allocation and task scheduling is realized; and the optimization capability and thesearch efficiency of the whole algorithm are improved.

Description

technical field [0001] The present invention relates to the fields of computer technology, information technology and system engineering, in particular to a cloud workflow optimization method, and more specifically, to a workflow optimization method based on a partial order adaptive 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 various types of computing resources and multiple tasks, and there are timing constraints between tasks. During execution, virtual machines are usually used as the smallest allocation unit of computing resources to receive and process these tasks. Cloud workflow execution or scheduling optimization refers to how to reasonably configur...

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Problems solved by technology

[0005] Aiming at the current optimization of cloud workflow execution, usually only from the perspective of resource configuration or task scheduling, the lack of an integrated collaborative optimization method for resource configuration and task scheduling, and the low performance of cloud workflow execution, the present invention provides a cloud computing The workflow optimization method based on partial order adaptive genetic algorithm in the environment effectively improves the execution performance of cloud workflow

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