A method and system for cloud computing task scheduling based on genetic algorithm

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

Active Publication Date: 2021-02-26
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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  • A method and system for cloud computing task scheduling based on genetic algorithm
  • A method and system for cloud computing task scheduling based on genetic algorithm
  • A method and system for cloud computing task scheduling based on genetic algorithm

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Embodiment Construction

[0059] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, 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 constitute a conflict with each other.

[0060] Genetic algorithm is a 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 require knowledge of the properties of the problem. It is widely used to solve NP-hard problems. The genetic algorithm simulates the phenomena of co...

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Abstract

The invention discloses a cloud computing task scheduling method based on a genetic algorithm, comprising: receiving a resource allocation request from a client, randomly generating a probability matrix λ for all subtasks according to the resource allocation request, and using a breadth-first search algorithm to perform step (1) In order to obtain multiple subtask sequences, assign each subtask in each subtask sequence to the physical machine corresponding to the maximum random probability value of the row of the task unit to which the subtask belongs in the probability matrix , and then form a parent population, calculate the time cost and energy cost of each physical machine processing the corresponding task unit, and obtain the total time cost and total energy of all physical machines corresponding to each element in the parent population according to the time cost and energy cost Overhead, thus forming a collection of vectors. The invention can solve the technical problem that the existing cloud computing field lacks an effective mechanism capable of simultaneously reducing cloud computing time overhead and cloud data center energy consumption.

Description

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

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Application Information

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Patent Type & Authority Patents(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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