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Abstract: P2P systems are categorized into tree-based and mesh-based systems according to their topologies. Mesh-based systems are considered more suitable for large-scale Internet applications, but require optimization on latency issue. This paper proposes a content subscribing mechanism (CSM) to eliminate unnecessary time delays during data relaying. A node can send content data to its neighbors as soon as it receives the data segment. No additional time is taken during the interactive stages prior to data segment transmission of streaming content. CSM consists of three steps. First, every node records its historical segments latency, and adopts gamma distribution, which possesses powerful expression ability, to express latency statistics. Second, a node predicts subscribing success ratio of every neighbor by comparing the gamma distribution parameters of the node and its neighbors before selecting a neighbor node to subscribe a data segment. The above steps would not increase latency as they are executed before the data segments are ready at the neighbor nodes. Finally, the node, which was subscribed to, sends the subscribed data segment to the subscriber immediately when it has the data segment. Experiments show that CSM significantly reduces the content data transmission latency.

[1] Banerjee, S., Bhattacharjee, B., Kommareddy, C., 2002. Scalable Application Layer Multicast. Proc. Conf. on Applications, Technologies, Architectures, and Protocols for Computer Communications. ACM Press, New York, p.205-217.

[2] Banerjee, S., Lee, S., Bhattacharjee, B., Srinivasan, A., 2003. Resilient Multicast Using Overlays. Proc. ACM SIGMETRICS Int. Conf. on Measurement and Modeling of Computer Systems. ACM Press, New York, p.102-113.

[3] Bawa, M., Deshpande, H., Garcia-Molina, H., 2003. Transience of peers & streaming media. SIGCOMM Comput. Commun. Rev., 33(1):107-112.

[4] Castro, M., Druschel, P., Kermarrec, A., Rowstron, A., 2002. SCRIBE: a large-scale and decentralized application-level multicast infrastructure. IEEE J. Selected Areas Commun., 20(8):1489-1499.

[5] Chu, Y.H., Rao, S.G., Zhang, H., 2000. A case for end system multicast. Meas. Model. Computer Syst., 6:1-12.

[6] Liu, L.S., Zimmermann, R., 2006. Adaptive low-latency peer-to-peer streaming and its application. Multimedia Systems Journal, 11(6):497-512.

[7] Pai, V.S., Kumar, K., Tamilmani, K., Sambamurthy, V., Mohr, A.E., 2003. Chainsaw: Eliminating Trees from Overlay Multicast. IPTPS, p.127-140.

[8] Ratnasamy, S., Handley, M., Karp, R., Shenker, S., 2001. Application Level Multicast Using Content-addressable Networks. Proc. 3rd Int. Workshop on Networked Group Communication. London, UK, p.14-29.

[9] Tran, D., Hua, K., Do, T., 2003. Zigzag: An Efficient Peer to Peer Scheme for Media Streaming. IEEE INFOCOM, p.1283-1293.

[10] Verma, S., Ooi, W.T., 2005. Controlling Gossip Protocol Infection Pattern Using Adaptive Fanout. Proc. IEEE ICDCS, p.665-674.

[11] Zhang, X.Y., Liu, J.C., Li, B., Yum, T.P., 2005. Coolstreaming/Donet: A Data-driven Overlay Network for Peer-to-Peer Live Media Streaming. Proc. IEEE INFOCOM, p.2102-2111.

[12] Zhang, M., Zhao, L., Tang, Y., Luo, J.G., Yang, S.Q., 2005. Large-scale Live Media Streaming Over Peer-to-Peer Networks through Global Internet. Proc. ACM Workshop on Advances in Peer-to-Peer Multimedia Streaming. ACM Press, New York, p.21-28.