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Genetic algorithm for spanning tree construction in P2P distributed interactive applications

机译:P2P分布式交互式应用中生成树构建的遗传算法

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摘要

Genetic algorithm (GA) has been widely used to generate useful solutions to optimization and search problems such as pattern analysis, recognition, classification and regression. In this paper, the GA will be used to build spanning tree in peer-to-peer Distributed Interactive Applications (DIAs) to minimize the total end-to-end delay. DIAs allow a group of users connected via a network to interact with a shared application state, which requires many-to-many communication among users. Peer-to-peer architectures have been proposed as an efficient and truly scalable solution for DIAs. The spanning tree topology has often been used to implement many-to-many communication in peer-to-peer DIAs. The peer incurred delay in the tree construction is often ignored or not well studied in the existing work. We show that the peer incurred delays are closely related to the topology of the spanning tree. By considering the peer incurred delay, the problem of building spanning tree with minimum total end-to-end delay to receivers in peer-to-peer DIAs is proven to be NP-complete. A genetic algorithm is proposed to approximate an optimal solution to the spanning tree topology. The proposed algorithm is evaluated by extensive experiments and the experimental results show the high efficiency of the proposed algorithm. (C) 2014 Elsevier B.V. All rights reserved.
机译:遗传算法(GA)已被广泛用于生成有用的解决方案,以优化和搜索问题,例如模式分析,识别,分类和回归。在本文中,GA将用于在对等分布式交互式应用程序(DIA)中构建生成树,以最大程度地减少总的端到端延迟。 DIA允许通过网络连接的一组用户与共享应用程序状态进行交互,这需要用户之间进行多对多通信。对等体系结构已被提出作为DIA的有效且真正可扩展的解决方案。生成树拓扑通常用于在对等DIA中实现多对多通信。在现有工作中,经常忽略或没有很好地研究对等方在树结构中引起的延迟。我们表明,对等点引起的延迟与生成树的拓扑密切相关。通过考虑对等点引起的延迟,在对等DIA中为接收者建立具有最小总端到端延迟的生成树的问题被证明是NP完全的。提出了一种遗传算法来近似生成树拓扑的最优解。通过大量实验对提出的算法进行了评估,实验结果表明该算法具有较高的效率。 (C)2014 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2014年第22期|185-192|共8页
  • 作者

    Li Yusen; Yu Jun; Tao Dapeng;

  • 作者单位

    Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore;

    Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China;

    S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510640, Guangdong, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Genetic algorithm; Optimization; P2P; Distributed interactive applications; Minimum latency;

    机译:遗传算法;优化;P2P;分布式交互式应用;最小等待时间;

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