@article{chiu_eun_2010, title={On the Performance of Content Delivery under Competition in a Stochastic Unstructured Peer-to-Peer Network}, volume={21}, ISSN={["1558-2183"]}, DOI={10.1109/tpds.2010.15}, abstractNote={Peer-to-peer (P2P) network is widely used for transferring large files nowadays. Measurement results show that most downloading peers are patient as the average download session is usually very long. It is sometimes even longer than downloading from a dedicated server using a modem. Existing results in the literature indicate that the stochastic fluctuation and the heterogeneity in the service capacity of each peer are two of the major reasons that make the average download time far longer than expected. In those studies, it has been often assumed that there is only one downloading peer in the network, ignoring the interaction and competition among peers. In this paper, we investigate the impact of the interaction and competition among peers on downloading performance under stochastic, heterogeneous, and unstructured P2P settings, thereby greatly extending the existing results on stochastic P2P networks made only under a single downloading peer in the network. To analyze the average download time in a P2P network with multiple competing downloading peers, we first introduce the notion of system utilization tailored to a P2P network. We investigate the relationship among the average download time, system utilization, and the level of competition among downloading peers in a stochastic P2P network. We then derive an achievable lower bound on the average download time and propose algorithms to give the peers the minimum average download time. Our result can much improve the download performance compared to earlier results in the literature. The performance of the different algorithms is compared under NS-2 simulations. Our results also provide theoretical explanation to the inconsistency of performance improvement by using parallel connections (parallel connections sometimes do not outperform a single connection) observed in some measurement studies.}, number={10}, journal={IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS}, author={Chiu, Yuh-Ming and Eun, Do Young}, year={2010}, month={Oct}, pages={1487–1500} }
 @article{chiu_eun_2008, title={Minimizing file download time in stochastic peer-to-peer networks}, volume={16}, ISSN={["1558-2566"]}, DOI={10.1109/TNET.2007.899051}, abstractNote={The peer-to-peer (P2P) file-sharing applications are becoming increasingly popular and account for more than 70% of the Internet's bandwidth usage. Measurement studies show that a typical download of a file can take from minutes up to several hours depending on the level of network congestion or the service capacity fluctuation. In this paper, we consider two major factors that have significant impact on average download time, namely, the spatial heterogeneity of service capacities in different source peers and the temporal fluctuation in service capacity of a single source peer. We point out that the common approach of analyzing the average download time based on average service capacity is fundamentally flawed. We rigorously prove that both spatial heterogeneity and temporal correlations in service capacity increase the average download time in P2P networks and then analyze a simple, distributed algorithm to effectively remove these negative factors, thus minimizing the average download time. We show through analysis and simulations that it outperforms most of other algorithms currently used in practice under various network configurations.}, number={2}, journal={IEEE-ACM TRANSACTIONS ON NETWORKING}, author={Chiu, Yuh-Ming and Eun, Do Young}, year={2008}, month={Apr}, pages={253–266} }