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{"references": ["L. Lao, J.-H. Cui, M. Gerla, and S. Chen, \"A scalable overlay multicast\narchitecture for large-scale applications,\" IEEE Trans. Parallel Distrib.\nSyst., vol. 18, no. 4, pp. 449-459, 2007.", "Y. Zhu, M.-Y. Wu, and W. Shu, \"Comparison study and evaluation of\noverlay multicast networks,\" in Proceedings of the 2003 International\nConference on Multimedia and Expo (ICME -03), 2003, pp. 493-496.", "Y.-h. Chu, S. G. Rao, and H. Zhang, \"A case for end system multicast\n(keynote address),\" in SIGMETRICS -00: Proceedings of the 2000 ACM\nSIGMETRICS international conference on Measurement and modeling\nof computer systems. New York, NY, USA: ACM, 2000, pp. 1-12.", "B. Williamson, Developing IP Multicast Networks Volume I. Cisco\nPress, 2000.", "L. H. Sahasrabuddhe and B. Mukhergee, \"Multicast routing algorithms\nand protocols: A tutorial,\" IEEE Network, vol. 14, no. 1, pp. 90-102,\nJan/Feb 2000.", "C. Diot, B. N. Levine, B. Lyles, H. Kassem, and D. Balensiefen,\n\"Deployment issues for the ip multicast service and architecture,\" IEEE\nNetwork, vol. 14, no. 1, pp. 78-88, Jan/Feb 2000.", "S. Birrer and F. E. Bustamante, \"A comparison of resilient overlay\nmulticast approaches,\" IEEE JOURNAL ON SELECTED AREAS IN\nCOMMUNICATIONS, vol. 25, no. 9, pp. 1695-1705, Dec. 2007.", "M. Guo and M. H. Ammar, \"Scalable live video streaming to cooperative\nclients using time shifting and video patching,\" in Proc. IEEE\nINFOCOM 2004. Hong Kong: IEEE, 11 2004, pp. 1501-1511.", "S. Birrer, D. Lu, F. E. Bustamante, Y. Qiao, and P. Dinda, \"Fatnemo:\nBuilding a resilient multi-source multicast fat-tree,\" in Proc. Ninth Int-l\nWorkshop Web Content Caching and Distribution (WCW 2004). LNCS,\nSept. 2004, pp. 182-196.\n[10] V. N. Padmanabhan, H. J. Wang, P. A. Chou, and K. Sripanidkulchai,\n\"Distributing streaming media content using cooperative networking,\"\nin NOSSDAV -02: Proceedings of the 12th international workshop on\nNetwork and operating systems support for digital audio and video.\nNew York, NY, USA: ACM, 2002, pp. 177-186.\n[11] D. A. Tran, K. A. Hua, and T. T. Do, \"A peer-to-peer architecture for\nmedia streaming,\" IEEE J. Selected Areas in Comm. (JSAC), vol. 22,\nno. 1, pp. 121-133, Jan. 2004.\n[12] K. Sripanidkulchai, B. Maggs, and H. Zhang, \"An analysis of live\nstreaming workloads on the internet,\" in IMC -04: Proceedings of the\n4th ACM SIGCOMM conference on Internet measurement. NewYork,\nNY, USA: ACM, 2004, pp. 41-54.\n[13] K. Sripanidkulchai, A. Ganjam, B. Maggs, and H. Zhang, \"The feasibility\nof supporting large-scale live streaming applications with dynamic\napplication end-points,\" in SIGCOMM -04: Proceedings of the 2004\nconference on Applications, technologies, architectures, and protocols\nfor computer communications. New York, NY, USA: ACM, 2004, pp.\n107-120.\n[14] M. Bawa, H. Deshpande, and H. Garcia-Molina, \"Transience of peers\n& streaming media,\" SIGCOMM Comput. Commun. Rev., vol. 33, no. 1,\npp. 107-112, 2003.\n[15] S. Banerjee, S. Lee, B. Bhattacharjee, and A. Srinivasan, \"Resilient\nmulticast using overlays,\" SIGMETRICS Perform. Eval. Rev., vol. 31,\nno. 1, pp. 102-113, 2003.\n[16] Y. Tian, D. Wu, G. Sun, and K.-W. Ng, \"Improving stability for peer-topeer\nmulticast overlays by active measurements,\" J. Syst. Archit., vol. 54,\nno. 1-2, pp. 305-323, 2008.\n[17] PPLive, .\n[18] Z. Fei and M. Yang, \"A proactive tree recovery mechanism for resilient\noverlay multicast,\" IEEE/ACM Trans. Netw., vol. 15, no. 1, pp. 173-186,\n2007.\n[19] G. Tan and S. A. Jarvis, \"Improving the fault resilience of overlay\nmulticast for media streaming,\" IEEE Trans. Parallel Distrib. Syst.,\nvol. 18, no. 6, pp. 721-734, 2007."]}
Network layer multicast, i.e. IP multicast, even after many years of research, development and standardization, is not deployed in large scale due to both technical (e.g. upgrading of routers) and political (e.g. policy making and negotiation) issues. Researchers looked for alternatives and proposed application/overlay multicast where multicast functions are handled by end hosts, not network layer routers. Member hosts wishing to receive multicast data form a multicast delivery tree. The intermediate hosts in the tree act as routers also, i.e. they forward data to the lower hosts in the tree. Unlike IP multicast, where a router cannot leave the tree until all members below it leave, in overlay multicast any member can leave the tree at any time thus disjoining the tree and disrupting the data dissemination. All the disrupted hosts have to rejoin the tree. This characteristic of the overlay multicast causes multicast tree unstable, data loss and rejoin overhead. In this paper, we propose that each node sets its leaving time from the tree and sends join request to a number of nodes in the tree. The nodes in the tree will reject the request if their leaving time is earlier than the requesting node otherwise they will accept the request. The node can join at one of the accepting nodes. This makes the tree more stable as the nodes will join the tree according to their leaving time, earliest leaving time node being at the leaf of the tree. Some intermediate nodes may not follow their leaving time and leave earlier than their leaving time thus disrupting the tree. For this, we propose a proactive recovery mechanism so that disrupted nodes can rejoin the tree at predetermined nodes immediately. We have shown by simulation that there is less overhead when joining the multicast tree and the recovery time of the disrupted nodes is much less than the previous works. Keywords
Network layer multicast, Fault Resilience, IP multicast
Network layer multicast, Fault Resilience, IP multicast
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