• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 高性能计算 • 上一篇    下一篇

一种云环境下基于混合型BBO的任务调度算法

童钊1,2,陈洪剑1,2,陈明1,2,梅晶1,2,刘宏1,2   

  1. (1.湖南师范大学信息科学与工程学院,湖南 长沙 410012;
    2.高性能计算与随机信息处理省部共建教育部重点实验室,湖南 长沙 410012)
  • 收稿日期:2017-05-15 修回日期:2017-08-15 出版日期:2018-05-25 发布日期:2018-05-25
  • 基金资助:

    国家自然科学基金(61502165);湖南省教育厅一般项目(17C0959)

A hybrid biogeography-based optimization
algorithm for task scheduling in cloud computing

TONG Zhao1,2,CHEN Hong-jian1,2,CHEN Ming1,2,MEI Jing1,2,LIU Hong1,2   

  1. (1.College of Information Science and Engineering,Hunan Normal University,Changsha 410012;
    2.Key Laboratory of High Performance Computing and Stochastic Information
    Processing(HPCSIP)(Ministry of Education of China),Changsha 410012,China)
     
     
  • Received:2017-05-15 Revised:2017-08-15 Online:2018-05-25 Published:2018-05-25

摘要:

任务调度在云计算中占有重要地位,是影响云计算性能的关键因素,被证明是NP问题。启发式算法是解决该问题的最有效方法之一,针对近年来出现的一种新型启发式算法——BBO算法展开研究,由于BBO算法在求解过程中收敛速度较慢,因此结合粒子群算法提出了一种新型算法的任务调度算法——HMBBO,并结合Cloudsim云仿真平台,进行了以Makespan为目标函数的比对实验。实验结果表明,与几种经典的启发式算法相比,HMBBO算法具有寻优能力强、收敛速度快、求解质量高的特点,为解决云计算环境中任务调度问题提供了一种新思路。

关键词: 云计算, 任务调度, BBO, Makespan

Abstract:

Task scheduling plays a critical role in cloud computing and is a key factor affecting the performance of cloud computing. It has been proved to be an NP problem. Heuristic algorithm is one of the most effective methods to solve this problem. This paper focuses on the Biogeography-Based Optimization (BBO) algorithm, which serves in recent years as a new heuristic algorithm. Because the BBO algorithm converges slowly in the solution process, by combining Particle Swarm Optimization (PSO) algorithm, we propose a novel task scheduling algorithm, named Hybrid Migrating Biogeography-Based Optimization (HMBBO). A comparison experiment using Makespan as the objective function is performed on the Cloudsim cloud simulation platform. The experiment results show that, compared with several classical heuristic algorithms, HMBBO has  the advantages of strong optimization ability, fast convergence speed and high-quality solution, and provides a new way to solving the task scheduling problem in cloud computing environment.

 

Key words: cloud computing, task scheduling, BBO, Makespan

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