基于群智能的多约束多路径QoS路由

Ankur Kulhari, C. Gandhi, Anil Jaiswal
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引用次数: 1

摘要

对于Internet上的某些应用,网络必须支持有保证的服务质量(QoS)。网络的鲁棒性对实现基本的QoS要求以支持实时应用起着重要的作用。虽然它已经通过各种单路径路由机制实现,但为了提供网络的鲁棒性和可用性,必须选择多条路径。根据各种指标选择路由。使用软计算技术,可以通过一次运行获得多条路径。本文提出了一种基于粒子群优化(PSO)的路由算法,以获得满足各种QoS参数约束的多条路径。结果与其他软计算技术如遗传算法和蚁群优化(ACO)进行了比较。
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Multi-constraint Multipath QoS Routing Using Swarm Intelligence
It is essential for a network to support guaranteed quality-of-service (QoS) for some applications on Internet. Robustness of the network plays an important role to achieve the basic QoS requirements to support real-time applications. Though it has been achieved through various single path routing mechanisms but to provide the robustness and availability to the network, multiple paths have to be selected. A route is selected based on various metrics. Using soft computing techniques capability of deriving multiple paths through a single run can be enabled. In this paper an implementation of particle swarm optimization (PSO), based routing algorithm to get multiple paths satisfying various constraints of QoS parameters is shown. The results are compared with other soft computing techniques like genetic algorithm and ant colony optimization (ACO).
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