Multi-workflow scheduling method based on multi-population hybrid intelligent optimization in cloud environment

A scheduling method and workflow technology, applied in energy-saving computing, genetic models, multi-programming devices, etc., can solve the problems of short running time of local search capabilities, lack of global search mechanism, easy to fall into local optimum, etc., to achieve enhanced global search Capabilities, Enhancing Diversity, Improving the Effects of Diversity

Active Publication Date: 2021-04-20
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Abstract
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Problems solved by technology

Among them, the particle swarm optimization algorithm has strong global search and fast convergence capabilities, but its local search performance is poor, and it is easy to fall into a local optimum during the iterative process; the simulated annealing algorithm has strong local search capabilities and short running time, but lacks effective global Search mechanism; genetic algorithm can maintain search diversity well, but it converges slowly and takes a long time to find the optimal solution

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  • Multi-workflow scheduling method based on multi-population hybrid intelligent optimization in cloud environment
  • Multi-workflow scheduling method based on multi-population hybrid intelligent optimization in cloud environment
  • Multi-workflow scheduling method based on multi-population hybrid intelligent optimization in cloud environment

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Embodiment

[0095] In order to test the effect of the multi-group hybrid intelligent optimization algorithm (MSC-HIO) proposed by the present invention for multi-workflow task scheduling in the cloud environment, the present invention uses the cloud computing simulation tool WorkflowSim, and selects three kinds of multi-objective optimization scheduling algorithms Contrast: non-dominated sorting genetic algorithm (NSGA-II), multi-objective ant colony algorithm (MOACS), endocrine-based multi-population co-evolutionary multi-objective optimization algorithm (ECMSMOO).

[0096] Select four types of workflows of medium scale, namely Montage_50, Inspiral_50, Epigenomics_46 and Cybershake_50, use 30 virtual machines with different processing capabilities, and perform scheduling simulation under 3 constraint factors (for example: 0.25, 0.5, 0.75) experiment. To avoid the randomness of scheduling results, each method was run 20 times for statistical analysis. The total execution time, total exec...

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Abstract

The invention discloses a multi-workflow scheduling method based on multi-population hybrid intelligent optimization in a cloud environment, and the method comprises the steps: respectively optimizing the total execution time and cost of a multi-workflow scheduling scheme through employing two populations, employing a third population, carrying out the proper balance of the optimization of the two targets; By focusing on searching different types of non-dominant solutions through the three populations, the diversity of elite solutions is improved, the defect that an existing intelligent optimization method is large in searching randomness is effectively overcome, and an optimal workflow scheduling scheme set can be found under the condition that the deadline condition of a user is met.

Description

technical field [0001] The invention belongs to the technical field of multi-workflow scheduling in a cloud environment, and in particular relates to a multi-workflow scheduling method based on multi-population hybrid intelligent optimization in a cloud environment. Background technique [0002] In recent years, cloud computing, as a new type of distributed computing and resource service provision mode, is being widely used. In particular, the advantages of cloud computing, such as pay-per-use and resource elastic configuration, enable cloud users to access configurable shared computing resource pools through the network without purchasing or maintaining any hardware resources such as local servers, and obtain computing power on demand. Storage space and information services provide a low-cost operating environment for workflow applications. Therefore, more and more complex scientific applications are being deployed or gradually migrated to cloud platforms for execution. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/455G06F9/50G06N3/12
CPCY02D10/00
Inventor 李慧芳王丹敬黄姜杭王一竹徐光浩邹伟东柴森春夏元清
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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