Underlay-unawareness in P2P systems can result in sub-optimal peer selection for overlay routing and hence poor performance. The majority of underlay aware proposals for peer selection focus on finding the shortest overlay routes by selecting the nearest peers according to proximity. However, in case of multiple and parallel downloads, if the underlay paths between a client and its selected nearest peers share a bottleneck, this can cause congestion, leading to performance deterioration instead of improvement. This effect was neglected in previous work because, in todays Internet, the bottleneck is usually not shared as it is the end users uplink. This is no longer the case in more modern scenarios such as FTTH or upcoming in-network caching techniques such as DECADE.
To address the above problem, this thesis proposes an improved peer selection approach for P2P applications called Fewest Common Hops (FCH) that ensures proximity based node selection having maximum path disjointness. It is a client based, infrastructure independent heuristic to optimize download speed for multiple and parallel downloads in P2P content distribution applications.
FCH was simulated for multiple downloads in a proximity based P2P application “Pas-try”with two underlay Models, “Rease”and “INET”. For parallel downloads FCH was simulated in BitTorrent. Simulations show that, even when FCH is implemented in the simplest possible fashion (using only ping), it can significantly decrease the download time. In general, the use of proximity along with path-disjointedness for peer selection decreases the file download time and increases network utilization in both homogeneous and heterogeneous situations.