Abstract: P2P file sharing applications are becoming more and more popular in Internet. They have deployed their own content delivery networks to facilitate the publishing and searching of files. A similarity-computing model is proposed for the peers in content delivery networks. The model fully mines the meta-information of files owned by peers, that is, the model calculates the similarity making use of file name, file size, file type according to different weights. The original problem of determining the model parameters is formulated as a constrained optimization problem, and the eMule application is taken as an instance to show how the model parameters can be determined. Since the similarity-computing model introduces the semantic information of peers, it can be applied to improve the physical topologies of content delivery networks, thus to improve the query and routing performance.

Key words: peer-to-peer network, similarity, optimization theory

摘要： P2P文件共享应用逐渐成为互联网中的主流应用，它们都部署了各自的内容分发网络用于文件的发布与查找。基于内容分发网络，提出了一个节点间相似度计算模型。模型充分挖掘了节点拥有的文件的元信息，在进行相似度计算时将文件名、文件长度、文件类型按照不同的权重进行计算。将模型的求参问题形式化为一个有约束的最优化问题，并以eMule应用为例，对其模型参数进行了确定。相似度计算模型引入了节点的语义信息，可应用于改善内容分发网络的物理拓扑，从而提高其查询性能与路由性能。

关键词: 对等网络, 相似度, 最优化理论