Targeted search: reducing the time and cost for searching for objects in multiple-server networks

In many applications-including peer-to-peer (P2P) file sharing, content distribution networks, and grid computing-a single object will be searched for in multiple servers. In this paper, we find the provably optimal search method for such applications and develop analytical models for search time and cost. A client node searching for objects maintains statistics on where (in which servers) it has previously found objects. Using these statistics to target future searches to popular servers is provably optimal. For object location and request distributions that are non-uniform, which has been shown to be the case in P2P file sharing networks, this method of targeted searching is found to be more cost effective (i.e., use less server resources) than broadcast-based searching. Our targeted search method is implemented in a prototype Gnutella servent called Ditella. Ditella can improve the scalability of file sharing in P2P networks and reduce the amount of traffic in the Internet by reducing file search query traffic.