Multi-interest clustering P2P network model
Liu Fang-ai · Jisuanji yingyong yanjiu · 2011
To reduce the routing hops of data retrieval in P2P network,proposed the MIKAD(multi-interest clustering KAD) network model.In the model,nodes' interest maintained by the documents cluster algorithm,through combining Kademlia and interesting-cluster together,and putting the nodes of similar interest in the neighboring position,which could improve routing efficiency in the peer-to-peer network.Simultaneously used synonymous characteristic of Keywords to lower the network complexity and improve retrieval accuracy.Simulation experimental results show that this model can achieve better search performance with the increase of nodes and data.