Indexing techniques for file sharing in scalable peer-to-peer networks

File sharing is a very popular service provided by peer-to-peer (P2P) networks. In a P2P file-sharing network, users share files and issue queries to the network to find the locations of files residing at other peer nodes. Recently, proxy-enabled peers, or supernodes, have been incorporated to enhance scalability by providing indexing services to nodes on slower network connections. Typically, supernodes build a vector or multi-index of shared files stored on other (slower) peer nodes connected to them. We consider a new model whereby the index tables of individual nodes are merged into a single data structure stored by the supernode. We analyze this model in relation to the standard vectorized data structure. We compare the performance of these supernode indexing algorithms and provide a theoretical analysis that is asymptotic and probabilistic in nature. However, there are several significant constant factors that the theory does not account for, and which are important for designing an optimal system solution. We report on a series of simulation experiments which provide verification of the asymptotic analysis of the formal framework and tools to determine the magnitude of the constant factors. Our general conclusion is that when the query rate exceeds the rate of data updates, the new merged model is preferable to the vector model. However, the details of our analysis allow us to consider combinations of several parameters, and thereby enable the design of optimal indexing schemes via the incorporation of measurements of the parameters of particular applications.