Luo Jiaqing

Adaptive Flooding Routing Algorithm in Unstructured P2P

Flooding is widely used in unstructured peer to peer (P2P) systems, such as Gnutella. Although it is effective in content search, flooding among peers or super-peers causes large volume of unnecessary traffic. To address this problem, we propose an efficient and adaptive search mechanism, adaptive flooding routing algorithm (AFRA). AFRA provides the flexibility to adaptively adjust the number of relay neighbors and TTL value to meet different performance requirements. The effectiveness of AFRA is demonstrated through simulation studies. Primary experimental results show that our new AFRA solution reduces about 65% of the flooding messages while maintaining the acceptable high searching quality

An Experimental Study of the Active Recommendation Mechanism Based Distributed Approximate Indexing in Unstructured P2P Networks

In unstructured P2P systems, it is hard to find the desired files without distributing queries, since there is neither a centralized directory nor any precise control over the network topology or file placement. Many valuable efforts have been done towards improving search efficiency and increasing the scalability of unstructured P2P systems while guaranteeing endurable resource consumptions. In this paper, we purpose an Active Recommendation Mechanism (ARM) which aims to provide efficient searching services and enhance benign competitions in P2P networks. We also build a two-tier proxy architecture consisting of reputation evaluating proxies and content indexing proxies. Based on the ARM and the new architecture, we purpose a Distributed Approximate Indexing (DAI) method to support an efficient search without the need for a single centralized index host.