摘要
为了在P2P环境中实现资源的更快更精确搜索,引入兴趣相似度计算方法,提出一种基于最近邻搜索算法的分组式P2P网络拓扑模型。在这个模型中,采用余弦相似性方法计算共享资源的相似程度;相似程度较高的节点形成朋友节点进行逻辑连接,兴趣相近的节点聚集成一个小组,结合缓存机制实现共享资源的高效搜索。模拟实验查询结果表明,兴趣相似度Sim值越大资源搜索越精确。模型中相似度的引入增强了P2P网络中资源定位的准确率,提高了搜索效率。
In order to search the resource of P2P environment faster and more accurate,introduces the similarity calculation method,and proposes a topology model based on nearest neighbor for P2P group networks.This model use the similarity cosine to calculate the similarity degree of sharing resources;High degree of similarity of the nodes make a logical connection,friend node in the node gathered near a group,combining the resources sharing caching mechanism high search.Simulation results show that the bigger the similarity Sim values,the more accurate the search of resources.The introduction of similarity enhances accuracy rate of P2P networks positioning,improves the searching efficiency.
出处
《计算机技术与发展》
2010年第11期100-104,108,共6页
Computer Technology and Development
基金
山东省自然科学基金(Y2007G11)
关键词
分组式P2P网络
兴趣域
相似度
缓存机制
搜索策略
P2P group networks
interest-domain
similarity
caching mechanism
search strategy
