Task Scheduling Method Based on Probabilistic Adaptive Ant Colony Optimization in Cloud Computing

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Task Scheduling Method Based on Probabilistic Adaptive Ant Colony Optimization in Cloud Computing

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[1]Wang Junying,Yan Fenfen,Chen Peng,et al.Task Scheduling Method Based on Probabilistic Adaptive Ant Colony Optimization in Cloud Computing[J].Journal of Zhengzhou University (Engineering Science),2017,38(04):51-56.[doi:10.13705/j.issn.1671-6833.2017.01.018]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 38卷 Number of periods: 2017 04 Page number: 51-56 Column: Public date: 2017-07-18

Title:: Task Scheduling Method Based on Probabilistic Adaptive Ant Colony Optimization in Cloud Computing

Author(s):: Wang Junying1; Yan Fenfen1; Chen Peng2; Dong Fangmin1; Zang Zhaoxiang2; 1. School of Computer and Information, Three Gorges University, Yichang, Hubei 443002; 2. Key Laboratory of Intelligent Visual Monitoring for Hydropower Engineering, Three Gorges University, Yichang, Hubei 443002

Keywords:: cloud computing; task scheduling; ant colony optimization; probability adaptive

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2017.01.018

Abstract:: The basic ant colony algorithm tended to be trapped in local optimum in solving task scheduling problems of cloud computing.A probability adaptive ant colony optimization was proposed.This algorithm rankd the tasks in descending order according to their size,defines the task concentration degree,and introduces the probability adaptive adjustment factor to adjust the assignment probability of over-concentrated resource noded.The results showed that the proposed algorithm shortened the task completion time,and had some improvements on convergence speed,compared with the Ant Colony Optimization and Modified Ant Colony Optimization.

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