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Cloud computing task scheduling method and system based on genetic algorithm

A technology of task scheduling and genetic algorithm, applied in genetic rules, computing, energy-saving computing, etc., can solve problems such as lack of

Active Publication Date: 2019-08-13
HUNAN UNIV
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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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  • Cloud computing task scheduling method and system based on genetic algorithm
  • Cloud computing task scheduling method and system based on genetic algorithm
  • Cloud computing task scheduling method and system based on genetic algorithm

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Embodiment Construction

[0059] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0060] Genetic algorithm is a kind of global optimization algorithm, it has been verified that it can effectively optimize multi-objective optimization problems, and has good universality. Unlike traditional optimization methods, genetic algorithms do not need to understand the characteristics of the problem. It is widely used in solving NP-hard problems. The genetic algorithm simulates competition, r...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06N3/12
CPCG06F9/5027G06F9/5072G06F9/5094G06N3/126Y02D10/00
Inventor 朱宁波刘元刘楚波全哲李肯立李克勤廖湘科
Owner HUNAN UNIV
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