Efficiency of Tree-structured Peer-to-peer Service Discovery Systems

Abstract : The efficiency of service discovery is a crucial point in the development of fully decentralized middlewares intended to manage large scale computational grids. The work conducted on this issue led to the design of many peer-to-peer fashioned approaches. More specifically, the need for flexibility and complexity in the service discovery has seen the emergence of a new kind of overlays, based on tries, also known as lexicographic trees. Although these overlays are efficient and well designed, they require a costly maintenance and do not accurately take into account the heterogeneity of nodes and the changing popularity of the services requested by users. In this paper, we focus on reducing the cost of the maintenance of a particular architecture, based on a dynamic prefix tree, while enhancing it with some load balancing techniques that dynamically adapt the load of the nodes in order to maximize the throughput of the system. The algorithms developed couple a self-organizing prefix tree overlay with load balancing techniques inspired by similar previous works undertaken for distributed hash tables. After some simulation results showing how our load balancing heuristics perform in such an overlay and compare to other heuristics, we provide a fair comparison of this architecture and similar overlays recently proposed.
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Communication dans un congrès
Hot-P2P 2008 - 5th International Workshop on Hot Topics in Peer-to-Peer Systems, Apr 2008, Miami, United States. IEEE, 2008 IEEE International Symposium on Parallel and Distributed Processing, pp.1-8, 〈10.1109/IPDPS.2008.4536198〉
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https://hal.inria.fr/hal-01428782
Contributeur : Eddy Caron <>
Soumis le : vendredi 6 janvier 2017 - 15:14:37
Dernière modification le : vendredi 22 juin 2018 - 01:19:52

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Eddy Caron, Frédéric Desprez, Cédric Tedeschi. Efficiency of Tree-structured Peer-to-peer Service Discovery Systems. Hot-P2P 2008 - 5th International Workshop on Hot Topics in Peer-to-Peer Systems, Apr 2008, Miami, United States. IEEE, 2008 IEEE International Symposium on Parallel and Distributed Processing, pp.1-8, 〈10.1109/IPDPS.2008.4536198〉. 〈hal-01428782〉

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