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    一种面向大规模P2P环境的成员管理机制

    A Membership Management Mechanism for Large Scale P2P Environment

    • 摘要: 基于P2P的系统都严重依赖于底层节点之间形成稳定的具有某种特征的拓扑结构.成员管理通过为节点维护可以直接访问的邻居视图,能够实现根据上层应用的语义组织节点拓扑.然而大规模P2P环境下节点的动态加入/退出、网络状况的动态波动、节点上资源的动态更新以及庞大的节点规模对成员管理的抗扰动性和可伸缩性提出了更高的要求.许多典型的成员管理技术要么忽略了系统的扰动问题,要么忽略了系统的伸缩问题,因而无法在大规模P2P环境下获得良好的效果.提出了一种新的成员管理机制,综合考虑多种系统资源动态变化的因素,通过抗扰动的成员发现协议以及可伸缩的成员维护方法,保证即使在恶劣环境下仍能够为上层应用维护稳定正确的节点拓扑结构.最后通过实验验证了所提出的成员管理机制在大规模P2P环境下的有效性,通过对实验数据的分析得出的结论为进一步的研究工作奠定了基础.

       

      Abstract: Node topology plays an important role in P2P-based systems. It serves as a basis to support application functions, and has major impact on their efficiency, cost and robustness. Membership management can construct node topology according to application’s semantic requirements by maintaining neighbor view on every node. However, large-scale P2P environment with the features of dynamic node joining/leaving, dynamic network condition fluctuation, dynamic resources varying and a large number of nodes, greatly challenges the perturbation-resistance and scalability of membership management. Many typical membership management techniques either ignored the issue of system perturbation, or ignored the issue of system size’s expansion/shrinking, and can’t work well in large-scale P2P environment. In this paper, a new membership management mechanism considering multiple factors of dynamic variation is given to maintain stable node topology in harsh environment. The proposed mechanism mainly consists of perturbation-resisted membership discovery protocol and scalable membership maintenance method. Experimental results verify the effectiveness of the proposed methods. Some useful conclusions obtained through the analysis of the experimental data lay a solid foundation for further research.

       

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