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Issue No. 08 - August (2011 vol. 22)
ISSN: 1045-9219
pp: 1342-1349
Zhenyu Li , Institute of Computing Technology, Chinese Academy of Sciences, Beijing
Gaogang Xie , Institute of Computing Technology, Chinese Academy of Sciences, Beijing
Kai Hwang , University of Southern California, Los Angeles
Zhongcheng Li , Institute of Computing Technology, Chinese Academy of Sciences, Beijing
Massive data dissemination is often disrupted by frequent join and departure or failure of client nodes in a peer-to-peer (P2P) network. We propose a new churn-resilient protocol (CRP) to assure alternating path and data proximity to accelerate the data dissemination process under network churn. The CRP enables the construction of proximity-aware P2P content delivery systems. We present new data dissemination algorithms using this proximity-aware overlay design. We simulated P2P networks up to 20,000 nodes to validate the claimed advantages. Specifically, we make four technical contributions: 1). The CRP scheme promotes proximity awareness, dynamic load balancing, and resilience to node failures and network anomalies. 2). The proximity-aware overlay network has a 28-50 percent speed gain in massive data dissemination, compared with the use of scope-flooding or epidemic tree schemes in unstructured P2P networks. 3). The CRP-enabled network requires only 1/3 of the control messages used in a large CAM-Chord network. 4) Even with 40 percent of node failures, the CRP network guarantees atomic broadcast of all data items. These results clearly demonstrate the scalability and robustness of CRP networks under churn conditions. The scheme appeals especially to web-scale applications in digital content delivery, network worm containment, and consumer relationship management over hundreds of datacenters in cloud computing services.
P2P networks, data dissemination, multicast algorithms, distributed systems, cloud computing.

G. Xie, K. Hwang, Z. Li and Z. Li, "Churn-Resilient Protocol for Massive Data Dissemination in P2P Networks," in IEEE Transactions on Parallel & Distributed Systems, vol. 22, no. , pp. 1342-1349, 2011.
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