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    乔百友 王国仁 丁琳琳. TBSN:一种基于分类层次的P2P网络[J]. 计算机研究与发展, 2008, 45(5): 803-809.
    引用本文: 乔百友 王国仁 丁琳琳. TBSN:一种基于分类层次的P2P网络[J]. 计算机研究与发展, 2008, 45(5): 803-809.
    Qiao Baiyou, Wang Guoren, and Ding Linlin. TBSN: A Taxonomy Hierarchy Based P2P Network[J]. Journal of Computer Research and Development, 2008, 45(5): 803-809.
    Citation: Qiao Baiyou, Wang Guoren, and Ding Linlin. TBSN: A Taxonomy Hierarchy Based P2P Network[J]. Journal of Computer Research and Development, 2008, 45(5): 803-809.

    TBSN:一种基于分类层次的P2P网络

    TBSN: A Taxonomy Hierarchy Based P2P Network

    • 摘要: 构建语义覆盖网络是支持基于语义的搜索、提高P2P网络查找性能和可扩展性的重要手段.现有的基于分类层次的P2P语义覆盖网络并不能充分利用分类层次所包含的语义信息,为此提出了一种基于分类层次的P2P网络(TBSN),该网络充分考虑遵循某种分类层次的数据源的特点,能够利用分类层次所包含的语义信息,动态地将peer节点聚簇成不同的语义簇,语义簇之间根据语义关系建立相应的语义路由,从而形成了一种基于语义的P2P网络.每个语义簇由一个superpeer节点和多个peer节点组成, 仅负责回答其语义子空间上的查询.查询根据语义首先被路由到可能有结果的语义簇中,然后转发给相关的peer节点,从而减少查询所涉及的节点和消息的数量,提高了网络的性能.实验表明,TBSN网络在查找性能和开销之间取得了良好的平衡,同时较好地保持了语义簇之间的负载平衡和簇中数据之间的语义关系.

       

      Abstract: Constructing semantic overlay networks is an important way to support semanticsbased search and enhance search performance and scalability of the P2P networks. The existing P2P semantic overlay networks based on the taxonomy hierarchies can not fully utilize the semantic information contained in the taxonomy hierarchies. Therefore, a taxonomy hierarchy based P2P network (TBSN) is presented in this paper, which fully considers the characteristics of data sources employing taxonomy hierarchy to describe the contents of their objects. It dynamically clusters peers into deferent semantic clusters based on the semantic information contained in the taxonomy hierarchy, and organizes the semantic clusters into semantic routing overlays, thus forming a semanticsbased P2P network. Each semantic cluster consists of a superpeer node and more peer nodes, and only responsible for answering queries in its semantic subspace. A query is firstly routed to the appropriate semantic clusters by an efficient searching algorithm, and then forwarded to the specific peers that hold the relevant data objects; so the peers involved and messages to send are reduced and the network performance is greatly enhanced. Preliminary evaluation shows that TBSN achieves a competitive tradeoff between search performance and overheads, and load balance among clusters and data semantics within a cluster is all well maintained.

       

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