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Finding K Shortest Paths in a Network Using Genetic Algorithm

机译:使用遗传算法在网络中查找k最短路径

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With the advent of new applications, different service needs come up. These needs could be in the form of reliability in delivering data, capacity amount in a particular range and certain amount of permissible delay. In order to provide high Quality of service to Networks, it is essential to provide a path between a given source and multiple destinations which satisfy certain constraints. For a domain catering to high QoS, there is a request of resources with certain constraints by all the applications. Speed and Scalability which are not flexible in terms of Network size and Topology are the basic issues to be considered here. Multimedia applications in general make use of k shortest paths whenever communication is to be carried out between a single source and one or more than one destination. In this paper, a genetic algorithm is used, which helps in determination of k shortest paths from a source node to more than one destination node, with bandwidth constraint. The algorithm makes use of the connection matrix as well as link bandwidth for determination of k shortest paths. The significance of using K shortest paths in a network is to increase Throughput and Packet delivery ratio.
机译:随着新应用的出现,不同的服务需求提出来。这些需求可以是在特定范围内提供数据的可靠性的形式,并且特定范围内的容量量和一定量的允许延迟。为了向网络提供高质量的服务,必须提供给定的源和多个令人满意的多个目的地之间的路径。对于迎合高QoS的域,所有应用程序都有一些约束的资源。在网络大小和拓扑方面不灵活的速度和可扩展性是这里要考虑的基本问题。每当要在单个源和一个或多个目的地之间执行通信时,多媒体应用程序通常会使用K最短路径。在本文中,使用遗传算法,其有助于确定从源节点到多于一个目的节点的K最短路径,带宽约束。该算法利用连接矩阵以及链路带宽来确定K最短路径。在网络中使用K最短路径的重要性是提高吞吐量和分组传递比率。

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