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Green Cloud Task-scheduling Algorithm Based on Improved BPSO

机译：基于改进BPSO的绿云任务调度算法

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摘要

Cloud computing is experiencing a rapid development since a large amount of data need to be addressed. How to carry on the reasonable task scheduling plays a vital role in the operating efficiency of cloud computing. This paper proposes a Green Cloud Task-scheduling Algorithm (GCTA) based on the improved Binary Particle Swarm Optimization (BPSO). This work avoids matrix operations by using a pipeline number for virtual machines and redefining the position and velocity of particle. Simulation results show that the proposed GCTA has less execution time, and reduces resource consumption accordingly.
机译：由于需要处理大量数据，因此云计算正在飞速发展。如何进行合理的任务调度对云计算的运营效率至关重要。本文提出了一种基于改进的二进制粒子群算法（BPSO）的绿云任务调度算法（GCTA）。这项工作通过为虚拟机使用管道编号并重新定义粒子的位置和速度来避免矩阵运算。仿真结果表明，提出的GCTA具有更少的执行时间，并相应地减少了资源消耗。

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  • 来源
    《Journal of information and computational science》 |2014年第12期|4301-4308|共8页
  • 作者

    Zhiyou Ouyang; Kun Wang; Lili Xu;

  • 作者单位

    Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003, China;

    Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003, China;

    Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003, China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Cloud Computing; Binary Particle Swarm Optimization; Task Scheduling Algorithm;

    机译：云计算;二元粒子群优化;任务调度算法;

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