Peer-to-peer systems have grown significantly in popularity over the last few years. An increasing number of research projects have been closely following this trend, looking at many of the paradigm's technical aspects. In the context of data-sharing services, efforts have focused on a variety of issues from object location and routing to fair sharing and peer lifespans. Overall, the majority of these projects have concentrated on either the whole P2P infrastructure or the client-side of peers. Little attention has been given to the peer's server-side, even when that side determines much of the everyday-user's experience. In this paper, we make the case for looking at the server-side of peers, focusing on the problem of scheduling download requests at the server-side of P2P systems with the intent of minimizing the average response time experienced by users. We start by characterizing server workload based on extensive trace collection and analysis. We then evaluate the performance and fairness of different scheduling policies through trace-driven simulations. Our results show that average response time can be dramatically reduced by more effectively scheduling the requests on the server-side of P2P systems.
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