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基于副本复制和Bloom Filter 的P2P 概率路由算法
引用本文:朱桂明,郭得科,金士尧. 基于副本复制和Bloom Filter 的P2P 概率路由算法[J]. 软件学报, 2011, 22(4): 773-781. DOI: 10.3724/SP.J.1001.2011.03757
作者姓名:朱桂明  郭得科  金士尧
作者单位:1. 国防科学技术大学,计算机学院,并行与分布处理国家重点实验室,湖南,长沙,410073
2. 国防科学技术大学,信息与管理学院,信息系统工程国家重点实验室,湖南,长沙,410073
基金项目:国家自然科学基金(60903206, 61070216); 国家重点基础研究发展计划(973)(2007CB310900); 国家高技术研究发展计划(863)(2011AA0123824001); 国防科学技术大学预研基金
摘    要:非结构化P2P网络资源定位过程中的查询延迟、查准率和查询成本难以同时被优化,为此,提出一种基于副本复制和Bloom Filter技术的P2P概率路由算法DCBF(data copying and Bloom Filter).DCBF基于有向随机网络,对资源对象进行少量的复制,并将各个副本随机路由给网络中的节点;接收副本的节点,以分布式衰减Bloom Filter向邻近节点传递副本的成员资格信息.理论分析和实验结果均表明,DCBF仅需复制少量的副本,通过以分布式衰减Bloom Filter传递副本的成员资格信息,使得网络中的绝大多数节点能够感知到副本的成员资格信息,从而使得各个节点能够以极低的查询代价,在较低的路由延迟范围内,高概率地将查询路由到目标节点.

关 键 词:对等计算  有向随机网络  副本复制  衰减BloomFilter  概率路由
收稿时间:2009-04-22
修稿时间:2009-10-22

P2P Probabilistic Routing Algorithm Based on Data Copying and Bloom Filter
ZHU Gui-Ming,GUO De-Ke and JIN Shi-Yao. P2P Probabilistic Routing Algorithm Based on Data Copying and Bloom Filter[J]. Journal of Software, 2011, 22(4): 773-781. DOI: 10.3724/SP.J.1001.2011.03757
Authors:ZHU Gui-Ming  GUO De-Ke  JIN Shi-Yao
Affiliation:National Laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology, Changsha 410073, China;National Laboratory for Information System Engineering, School of Information System and Management, National University of Defense Technology, Changsha 410073, China;National Laboratory for Parallel and Distributed Processing, School of Computer, National University of Defense Technology, Changsha 410073, China
Abstract:It is hard to optimize query latency, query hit, and query cost at the same time for the resource location of unstructured peer-to-peer network. For this problem, this paper presents a probabilistic routing algorithm called DCBF (data copying and Bloom Filter), which is based on data copying and a Bloom Filter technique. DCBF makes a few copies of each shared resource and places each copy on a random selected node, based on a directed random network. Each node forwards membership information to neighboring nodes with distributed declining Bloom Filters. Analysis and experimental results show that DCBF can make the most of the nodes, use the membership information of resource objects by making only a few copies, and forward membership information with distributed declining Bloom Filter to achieve high query hits with low cost and low latency.
Keywords:peer-to-peer computing   directed random network   data copying   decaying Bloom Filter  probabilistic routing
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