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Resource Scheduling Strategy Method Based on Genetic Taboo Hybrid Algorithm in Private Cloud Environment

A technology of resource scheduling and hybrid algorithm, applied in the field of computer resource scheduling strategy, can solve the problems of strong dependence and low efficiency, and achieve the effect of not being easily destroyed, reducing the violation rate, and improving the optimization of resource allocation.

Inactive Publication Date: 2018-11-13
BEIJING JIAOTONG UNIV
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Problems solved by technology

It has the advantages of strong local search ability, fast convergence speed, and strong "mountain climbing" ability, but the disadvantage of the tabu search algorithm is that its search performance is highly dependent on the initial solution, and the iterative process of the tabu search is serial, only for The movement of a single state, when a large number of resource scheduling tasks are executed in the cloud environment, its efficiency is much lower than that of parallel algorithms

Method used

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  • Resource Scheduling Strategy Method Based on Genetic Taboo Hybrid Algorithm in Private Cloud Environment
  • Resource Scheduling Strategy Method Based on Genetic Taboo Hybrid Algorithm in Private Cloud Environment
  • Resource Scheduling Strategy Method Based on Genetic Taboo Hybrid Algorithm in Private Cloud Environment

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Embodiment 1

[0046] Embodiment 1: as figure 1 , figure 2 , image 3 and Figure 4 As shown, the resource scheduling strategy method based on the genetic taboo hybrid algorithm in the private cloud environment contains the following steps;

[0047] The first step: initial population generation.

[0048] The algorithm and parameters are given, and the number of iterations, initial population, crossover probability, and mutation probability are set. and code the individual. The encoding process is abstracted as distributing n virtual machines to m physical nodes, first generating a random sequence containing n virtual machine numbers, and then applying the multidimensional priority adaptation algorithm (First Fit, FF) to sequentially put the random sequence numbers into the physical nodes. In the server, the chromosome code is obtained. According to this method, the attached figure 1 The chromosome code obtained in is: {2213241421}. Repeat the priority adaptation algorithm (First Fit, ...

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Abstract

The invention discloses a genetic-tabu hybrid algorithm based resource scheduling policy in a private cloud environment. The policy comprises the steps of step 1: randomly generating an initial population; step 2: judging whether the population meets an algorithm stop condition or not, and if yes, then outputting an optimal solution; step 3: calculating fitness function values of all individuals in the population; step 4: selecting a next-generation population by adopting an optimal individual reservation method and tournament method selection policy; step 5: performing crossover on selected individuals according to a crossover probability to generate two offspring individuals; step 6: performing mutation operation according to a mutation probability to generate new offspring individuals; step 7: optimizing offspring individuals generated by using a genetic algorithm through a tabu search algorithm; and step 8: generating a new-generation population and returning to the step 2. According to the invention, the resource scheduling policy with good globality and parallelism is designed, so that a prematurity phenomenon of the genetic algorithm is avoided.

Description

technical field [0001] The invention relates to a resource scheduling strategy method based on a genetic taboo hybrid algorithm in a private cloud environment, and belongs to the technical field of computer resource scheduling strategies. Background technique [0002] Cloud computing is a network resource sharing mode that distributes computing on a large number of distributed computers or remote servers, switches resources to required applications according to the Internet operation mode, and accesses computers and storage systems according to requirements. In this shared model, "cloud" refers to various virtualized computing resource pools, including various infrastructures for constructing applications, as well as specific cloud computing applications on these infrastructures. Virtualization technology can build virtual resources on actual hardware resources to achieve elasticity and dynamics. [0003] Using virtualization technology: [0004] 1. It can maximize the uti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/50G06N3/12
Inventor 徐维祥赵博贾琳
Owner BEIJING JIAOTONG UNIV
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