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Online and offline based load balance algorithm in cloud computing

机译:云计算中基于在线和离线的负载均衡算法

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摘要

Cloud Computing (CC) makes it possible for a common user to get an access to large pools of data and computational resources through a variety of interfaces. Among the so many important problems in CC, load balancing technique has been paid more and more attention for its important role. Good load balance algorithms can make whole system run more efficient. A new load balancing method combined with the advantage of online and offline load balancing algorithms are proposed in this paper. Two choice algorithm and its improvement are used in the online step. Bacteria Foraging Optimization (BFO) and its improvement motivated by Lamarck Evolutionary Theory are introduced in our offline step. Online load balancing uses imperfect information, aiming at finishing tasks as fast as possible; while the offline makes full use of all information to make a supplement. Experiments on the heterogeneous tasks and serving points for computation intensive loads have been used here and the good performance shows the efficiency of our proposed method. (C) 2017 Elsevier B.V. All rights reserved.
机译:云计算(CC)使普通用户可以通过各种接口访问大型数据和计算资源池。在CC的众多重要问题中,负载均衡技术的重要作用越来越受到关注。好的负载平衡算法可以使整个系统更高效地运行。结合在线和离线负载均衡算法的优点,提出了一种新的负载均衡方法。在线步骤中使用了两种选择算法及其改进。我们的离线步骤介绍了细菌觅食优化(BFO)及其由Lamarck进化理论推动的改进。在线负载平衡使用不完善的信息,旨在尽快完成任务。线下则充分利用所有信息来补充。这里使用了针对计算密集型负载的异构任务和服务点的实验,并且良好的性能表明了我们提出的方法的效率。 (C)2017 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Knowledge-Based Systems 》 |2017年第15期| 91-104| 共14页
  • 作者单位

    Harbin Inst Technol, Shenzhen Grad Sch, Comp Sci & Technol, Room 106,Bldg C, Shenzhen 518055, Peoples R China;

    Harbin Inst Technol, Shenzhen Grad Sch, Comp Sci & Technol, Room 106,Bldg C, Shenzhen 518055, Peoples R China;

    Harbin Inst Technol, Shenzhen Grad Sch, Comp Sci & Technol, Room 106,Bldg C, Shenzhen 518055, Peoples R China;

    Harbin Inst Technol, Shenzhen Grad Sch, Comp Sci & Technol, Room 106,Bldg C, Shenzhen 518055, Peoples R China;

    Zhejiang Univ, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, Peoples R China;

    Texas Tech Univ, 2500 Broadway, Lubbock, TX 79409 USA;

    Harbin Inst Technol, Shenzhen Grad Sch, Comp Sci & Technol, Room 106,Bldg C, Shenzhen 518055, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cloud computing; Bacteria foraging optimization algorithm; Load balance;

    机译:云计算;细菌觅食优化算法;负载均衡;

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