| A Routing Algorithm for Risk.Scanning Agents Using Ant Colony Algorithm in P2P Network |
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| 作者姓名： | TANG Zhuo LU Zhengding LI Ruixuan |
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| 作者单位： | College of Computer Science and Technology, HuazhongUniversity of Science and Technology, Wuhan 430074,H ubei, China |
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| 基金项目： | 国家自然科学基金;湖北省自然科学基金 |
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| 摘 要： | This paper describes a routing algorithm for risk scanning agents using ant colony algorithm in P2P（peerto peer） network. Every peer in the P2P network is capable of updating its routing table in a real-time way, which enables agents to dynamically and automatically select, according to current traffic condition of the network, the global optimal traversal path. An adjusting mechanism is given to adjust the routing table when peers join or leave. By means of exchanging pheromone intensity of part of paths, the algorithm provides agents with more choices as to which one to move and avoids prematurely reaching local optimal path. And parameters of the algorithm are determined by lots of simulation testing. And we also compare with other routing algorithms in unstructured P2P network in the end.
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| 关 键 词： | P2P 蚁群算法 信息安全 电子算法 风险 |
| 文章编号： | 1007-1202（2006）05-1097-07 |
| 收稿时间： | 2006-03-25 |
A routing algorithm for risk-scanning agents using ant colony algorithm in P2P network |
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| TANG Zhuo LU Zhengding LI Ruixuan.A Routing Algorithm for Risk.Scanning Agents Using Ant Colony Algorithm in P2P Network[J].Wuhan University Journal of Natural Sciences,2006,11(5):1097-1103. |
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| Authors: | Tang Zhuo Lu Zhengding Li Ruixuan |
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| Institution: | (1) College of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China |
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| Abstract: | This paper describes a routing algorithm for risk-scanning agents using ant colony algorithm in P2P(peer-to peer) network. Every peer in the P2P network is capable of updating its routing table in a real-time way, which enables agents to dynamically and automatically select, according to current traffic condition of the network, the global optimal traversal path. An adjusting mechanism is given to adjust the routing table when peers join or leave. By means of exchanging pheromone intensity of part of paths, the algorithm provides agents with more choices as to which one to move and avoids prematurely reaching local optimal path. And parameters of the algorithm are determined by lots of simulation testing. And we also compare with other routing algorithms in unstructured P2P network in the end. |
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| Keywords: | risk ant colony algorithm P2P |
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