Cloud workflow scheduling optimization method based on hierarchy and load balancing genetic algorithm

Abstract

The invention discloses a cloud workflow scheduling optimization method based on a hierarchy and load balancing genetic algorithm. The cloud workflow scheduling optimization method comprises the following steps: obtaining information required by scheduling optimization; calculating a hierarchical value of the task; initializing a contemporary population; carrying out evolution: carrying out crossover operation to form a new population, carrying out mutation operation on the new population, carrying out decoding to calculate a fitness value, carrying out improvement by using a hierarchy and load balancing method, and selecting N different individuals from the contemporary population and the new population to form a new contemporary population until an evolution termination condition is met;and outputting a scheduling optimization scheme. According to the cloud workflow scheduling optimization method, on the premise that global search is achieved, serial individual decoding based on aninsertion mode, individual improvement based on hierarchy and load balancing, parameterization uniform crossing based on preference and other methods are adopted, and the optimization capacity and search efficiency of the 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 scheduling optimization method, more specifically, to a cloud workflow scheduling optimization method based on hierarchical and load balancing 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. 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 user n...

AI Technical Summary

Problems solved by technology

[0011] In order to overcome that 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 and the incompleteness of the search space of the existing intelligent computing method based on hierarchical coding, based on the global search The intelligent calculation method will lead to the decrease of search efficiency and other deficiencies. The present invention provides a cloud workflow scheduling optimization method based on hierarchical and load balancing genetic algorithm, which effectively improves the efficiency and quality of the solution.

Images