In this paper we present an empirical study of a workload gathered by crawling the eDonkey network --- a dominant peer-to-peer file sharing system --- for over 50 days.We first confirm the presence of some known features, in particular the prevalence of free-riding and the Zipf-like distribution of file popularity. We also analyze the evolution of document popularity.We then provide an in-depth analysis of several clustering properties of such workloads. We measure the geographical clustering of peers offering a given file. We find that most files are offered mostly by peers of a single country, although popular files don't have such a clear home country.We then analyze the overlap between contents offered by different peers. We find that peer contents are highly clustered according to several metrics of interest.We propose to leverage this property by allowing peers to search for content without server support, by querying suitably identified semantic neighbours. We find via trace-driven simulations that this approach is generally effective, and is even more effective for rare files. If we further allow peers to query both their semantic neighbours, and in turn their neighbours' neighbours, we attain hit rates as high as over 55% for neighbour lists of size 20.

Today data sources are pervasive and their number is growing tremendously. Current tools are not prepared to exploit this unprecedented amount of information and to cope with this highly heterogeneous, autonomous and dynamic environment. In this paper, we propose a novel semantic overlay network architecture, PARIS, aimed at addressing these issues. In PARIS, the combination of decentralized semantic data integration with gossip-based (unstructured) overlay topology management and (structured) distributed hash tables provides the required level of flexibility, adaptability and scalability, and still allows to perform rich queries on a number of autonomous data sources. We describe the logical model that supports the architecture and show how its original topology is constructed. We present the usage of the system in detail, in particular, the algorithms used to let new peers join the network and to execute queries on top of it and show simulation results that assess the scalability and robustness of the architecture.