Feverfew: a scalable coverage-based hybrid overlay for Internet-scale pub/sub networks  

作　　者：MA XingKong WANG YiJie SUN WeiDong 

机构地区：[1]National Key Laboratory for Parallel and Distributed Processing, School of Computer,National University of Defense Technology

出　　处：《Science China(Information Sciences)》2014年第5期47-60,共14页中国科学（信息科学）（英文版）

基　　金：supported by National Grand Fundamental Research 973 Program of China(Grant No.2011CB30-2601);National Natural Science Foundation of China(Grant No.61379052);National High-tech R&D Program of China(863)(Grant No.2013AA01A213);Natural Science Foundation for Distinguished Young Scholars of Hunan Province(Grant No.S2010J5050);Specialized Research Fund for the Doctoral Program of Higher Education(Grant No.20124307110015)

摘　　要：The publish/subscribe （pub/sub） paradigm is a popular communication model for data dissemina- tion in large-scale distributed networks. However, sealability comes with a contradiction between the delivery latency and the memory cost. On one hand, constructing a separate overly per topic guarantees real-time dis- semination, while the number of node degrees rapidly increases with the number of subscriptions. On the other hand, maintaining a bounded number of connections per node guarantees small memory cost, while each message has to traverse a large number of uninterested nodes before reaching the subscribers. In this paper, we propose Feverfew, a coverage-based hybrid overlay that disseminates messages to all subscribers without uninterested nodes involved in, and increases the average number of node connections slowly with an increase in the number of subscribers and nodes. The major novelty of Feverfew lies in its heuristic coverage mechanism implemented by combining a gossip-based sampling protocol with a probabilistie searching protocol. Based on the practical workload, our experimental results show that Feverfew significantly outperforms existing coverage-based overlay and DHT-based overlay in various dynamic network environments.The publish/subscribe （pub/sub） paradigm is a popular communication model for data dissemina- tion in large-scale distributed networks. However, sealability comes with a contradiction between the delivery latency and the memory cost. On one hand, constructing a separate overly per topic guarantees real-time dis- semination, while the number of node degrees rapidly increases with the number of subscriptions. On the other hand, maintaining a bounded number of connections per node guarantees small memory cost, while each message has to traverse a large number of uninterested nodes before reaching the subscribers. In this paper, we propose Feverfew, a coverage-based hybrid overlay that disseminates messages to all subscribers without uninterested nodes involved in, and increases the average number of node connections slowly with an increase in the number of subscribers and nodes. The major novelty of Feverfew lies in its heuristic coverage mechanism implemented by combining a gossip-based sampling protocol with a probabilistie searching protocol. Based on the practical workload, our experimental results show that Feverfew significantly outperforms existing coverage-based overlay and DHT-based overlay in various dynamic network environments.

关 键 词：PUBLISH/SUBSCRIBE coverage-based data dissemination topic-based gossip 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]