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基于Agent和蚁群算法的分布式服务发现

期刊名称：软件学报
时间：0
页码：1795-1809
语言：中文
分类：TP311[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
作者机构：[1]东南大学计算机科学与工程学院,江苏南京210096, [2]安徽工业大学计算机学院,安徽马鞍山243002
相关基金：Supported by the National Natural Science Foundation of China under Grant Nos.60773103, 60903161, 60903162, 90912002 （国家自然科学基金）; the National Basic Research Program of China under Grant No.2010CB328104 （国家重点基础研究发展计划（973））; the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.200802860031 （高等学校博士学科点专项科研基金）; the Jiangsu Provincial Natural Science Foundation of China under Grant Nos.BK2007708, BK2008030 （江苏省自然科学基金）; the Jiangsu Provincial Key Laboratory of Network and Information Security of China under Grant No.BM2003201 （江苏省网络与信息安全重点实验室）; the Key Laboratory of Computer Network and Information Integration （Southeast University）, Ministry of Education of China under Grant No.93K-9 （东南大学计算机网络和信息集成教育部重点实验室）
相关项目：AMS数据计算环境应用示范

关键词：服务发现, PEER-TO-PEER网络, AGENT, 蚁群算法, 路由机制, service discovery, peer to peer network, agent, ant colony algorithm, routing mechanism

中文摘要：

提出一种类似蚂蚁觅食活动的Agent服务发现机制．有两类Agent合作寻找目标服务：Search Agent和Guide Agent．前者模拟蚂蚁的行为在网络上发现目标服务，后者管理一个由信息素和跳数组成的服务路由表,用以指导Search Agent的行进路线．动态变化的信息素可以让Search Agent感知到网络拓扑和服务资源的变化，而跳数可以让它们了解距离．路由选择中还使用语义相似度作为启发因子，用于提高召回率．Search Agent生命周期控制机制使查询流量负载成为可控的，并具有确定的上界．实验结果表明，该方法在大规模的分布式计算环境下具有良好的可扩展性和动态环境下的适应性．

英文摘要：

This paper suggests an ant-like agent service discovery mechanism. There are two types of agents cooperating to search target services： Search Agent and Guide Agent. Search Agent simulates the behavior of an ant that searches for services on the network. Guide Agent is responsible to manage a service route table that consists of pheromone and hop count, instructing Search Agent＇s routing. Volatile pheromones make Search Agent sense the change of topology and service resource, and hop count makes them know the distance. Semantic similarity is also introduced in routing selection as a heuristic factor, which improves the recall. The life-span control policy makes query traffic controllable. With system size increasing, the query traffic would increase slightly and has an upper bound. The result of simulation shows that the suggested mechanism is scalable and adaptable enough to be suitable for large-scale dynamic computing environments.

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