Two-stage cloud workflow scheduling optimization method of hybrid heuristic algorithm and genetic algorithm

Abstract

The invention discloses a two-stage cloud workflow scheduling optimization method of a hybrid heuristic algorithm and a genetic algorithm. The method comprises the following steps: acquiring information required by scheduling; initializing a population based on a load balancing key task priority method; in two stages: in the stage 1, in combination with a heuristic method of key task priority scheduling, rapidly converging an algorithm near an optimal solution through virtual machine allocation list crossover mutation operation, and in the stage 2, carrying out neighborhood expansion search through crossover mutation operation of a virtual machine allocation list and a task scheduling sequence list to find the optimal solution; outputting a scheduling optimization scheme; adopting an integer coding method based on topological sorting and a serial individual decoding method based on an insertion mode in evolution, and using an FBI & D method and an LDI method to improve population. Compared with the method, the search efficiency and the optimization capability 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 scheduling optimization method, more specifically, to a two-stage cloud workflow scheduling optimization method that mixes heuristics and genetic algorithms. Background technique [0002] Workflow under the cloud computing environment, referred to as "cloud workflow", is the integration of cloud computing and workflow-related technologies, and has a wide range of applications in cross-organizational business collaboration and scientific computing that require efficient computing performance and large-scale storage support. prospect. 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 allocate the tasks in the...

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Problems solved by technology

[0011] In order to overcome the problems that the quality of the heuristic method solution is usually not very high and depends on the type of workflow, while the intelligent calculation method based on global search will lead to a decrease in search efficiency and low efficiency of single-stage evolution, the present invention provides a hybrid The two-stage cloud workflow scheduling optimization method based on heuristic and genetic algorithm effectively improves the efficiency and quality of the solution

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