• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Wang Wentao, Wu Junmin, Xu Yinlong, Li Huanghai, and Bao Chunjian. A Hierarchical Group Communication Protocol for Scalable Total Ordering[J]. Journal of Computer Research and Development, 2006, 43(10): 1775-1781.
Citation: Wang Wentao, Wu Junmin, Xu Yinlong, Li Huanghai, and Bao Chunjian. A Hierarchical Group Communication Protocol for Scalable Total Ordering[J]. Journal of Computer Research and Development, 2006, 43(10): 1775-1781.

A Hierarchical Group Communication Protocol for Scalable Total Ordering

More Information
  • Published Date: October 14, 2006
  • In parallel and distributed systems, a great deal of members in a group are cooperating to achieve some functions. But in a traditional group communication system, there are lots of communication overheads, especially when membership of group changes frequently. These overheads will greatly degrade the efficiency of group communication system. In this paper, a novel hierarchical group communication protocol called RHGP is proposed. RHGP is the acronym of “ring-based hierarchical of group protocol”. This protocol supports total order message delivery and hierarchical group management by using token passing. It also supports dynamical changing of the membership of a group. In order to reduce communication overheads and improve reliability, the protocol decreases the number of messages exchanged during the membership changing of a group. It is proved that the proposed protocol is reliable in the sense that with high probability of 99.8646% a ring-based hierarchy with nearly 200 members can work well when member faulty probability is bounded by 0.1%; if at most 3 members faulty are allowed, reliability probability of hierarchy is 99.9999%. It is also proved that the proposed protocol is scalable in the sense that with the number of group members increasing, reliability probability of hierarchy decreases slowly.
  • Related Articles

    [1]Wang Xu, Chen Qiang, Sun Quansen. Multichannel Spectral-Spatial Total Variation Model for Diffractive Spectral Image Restoration[J]. Journal of Computer Research and Development, 2020, 57(2): 413-423. DOI: 10.7544/issn1000-1239.2020.20190333
    [2]Wu Weizhi, Gao Cangjian, Li Tongjun. Ordered Granular Labeled Structures and Rough Approximations[J]. Journal of Computer Research and Development, 2014, 51(12): 2623-2632. DOI: 10.7544/issn1000-1239.2014.20131048
    [3]Te Rigen, Li Wei, and Li Xiongfei. Storage Model and Implementation of the Dynamic Ordered Tree[J]. Journal of Computer Research and Development, 2013, 50(5): 969-985.
    [4]Yang Xin, Zhou Dake, Fei Shumin. A Self-Adapting Bilateral Total Variation Technology for Image Super-Resolution Reconstruction[J]. Journal of Computer Research and Development, 2012, 49(12): 2696-2701.
    [5]Mao Yuxing and Shi Baile. An Incremental Method for Mining Generalized Association Rules Based on Extended Canonical-Order Tree[J]. Journal of Computer Research and Development, 2012, 49(3): 598-606.
    [6]Liu Runtao, Hao Zhongxiao. A Multi-Order Based Index Structure for Spatial Data—MOIS-tree[J]. Journal of Computer Research and Development, 2010, 47(5): 849-857.
    [7]Wan Jing, Wang Xiaoyu, Hao Zhongxiao. Study on Membership of Mixed Dependency Set in Strong Totally Ordered Temporal Scheme[J]. Journal of Computer Research and Development, 2009, 46(6): 1028-1035.
    [8]Wan Jing, Hao Zhongxiao. Study of Multi-Valued Dependency in Strong Total Order Temporal Scheme with Multiple Time Granularities[J]. Journal of Computer Research and Development, 2008, 45(6).
    [9]Li Lei, Wang Huaimin, and Shi Dianxi. A High Performance Total Order Broadcast Algorithm[J]. Journal of Computer Research and Development, 2007, 44(9): 1449-1455.
    [10]Deng Yanjun and Xu Xuezhou. Formal Specification and Verification for Group Communication Algorithm Suiting Extended Virtual Synchrony[J]. Journal of Computer Research and Development, 2005, 42(4): 676-683.

Catalog

    Article views (753) PDF downloads (465) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return