Cloud computing task scheduling method and system based on genetic algorithm

Abstract

The invention discloses a cloud computing task scheduling method based on a genetic algorithm. The method comprises the steps of receiving a resource allocation request from a client, randomly generating a probability matrix Lambda for all the sub-tasks according to the resource allocation request, processing the task dependency graph in the step (1) by adopting a breadth-first search algorithm; therefore, acquiring a plurality of sub-task sequences; sequentially allocating each sub-task in each sub-task sequence to a physical machine corresponding to the maximum random probability value of the row where the task unit to which the sub-task belongs in the probability matrix is located; further forming a parent population, calculating the time cost and the energy cost of each physical machine for processing the corresponding task unit, and obtaining the total time cost and the total energy cost of all the physical machines corresponding to each element in the parent population accordingto the time cost and the energy cost so as to form a vector set. The technical problem that an effective mechanism capable of reducing the cloud computing time cost and the cloud data center energy consumption at the same time is lacked in the existing cloud computing field can be solved.

Description

Technical field [0001] The present invention belongs to the technical field of cloud computing, and more specifically, relates to a cloud computing task scheduling method and system based on genetic algorithms. Background technique [0002] With the popularization of Internet access and the "3V" nature of data presented in the network (ie, high speed (Velocity), large volume (Volume) and diversity (Variety)), cloud computing has become more important in industry, academia, and society. The more important it is. Generally speaking, cloud computing consists of distributed computing, grid computing, utility computing, and autonomous computing. It provides on-demand computing and storage services with high performance and high scalability. However, with the continuous increase of the amount of calculation in the cloud computing process, the energy consumption of the cloud data center also continues to rise accordingly, which has become a prominent problem in the cloud computing fiel...

AI Technical Summary

Problems solved by technology

Its purpose is to solve the technical problem that the existing cloud computing field lacks an effective mechanism that can simultaneously reduce cloud computing time overhead and cloud data center energy consumption

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