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Selection and ranking of optimal routes through genetic algorithm in a cognitive routing system for mobile ad-hoc network

机译:移动自组织网络认知路由系统中遗传算法的最优路由选择与排序

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Genetic algorithm can be used for proper selection and ranking of all possible variable route addresses in mobile ad-hoc network (MANET). Ranking is based upon priority code of the links. A priority code is calculated by respective routing protocol, which depends on different parameters and metrics. A node can change its position and new nodes may join the MANET, so genetic algorithm can better estimate such kind of variations through its crossover and mutation genetic operators. Genetic algorithm is especially useful in cases of novel cognitive routing for MANET. Cognition in MANET is either based upon learning automata method as in some wireless sensor networks or specialized cognitive neural networks. Ranking of optimal links in MANET after a regular interval through genetic algorithm enhance the performance of cognitive routing. It help in proper selection of desired routing protocol for a given set of network conditions.
机译:遗传算法可用于在移动自组织网络(MANET)中对所有可能的可变路由地址进行适当的选择和排名。排名基于链接的优先级代码。优先级代码由相应的路由协议计算,这取决于不同的参数和度量。一个节点可以改变其位置,新的节点可以加入MANET,因此遗传算法可以通过其交叉和变异遗传算子更好地估计这种变异。遗传算法在用于MANET的新颖认知路由的情况下尤其有用。 MANET中的认知要么基于某些无线传感器网络中的学习自动机方法,要么基于专门的认知神经网络。通过遗传算法在规则间隔后对MANET中的最佳链接进行排名可以增强认知路由的性能。对于一组给定的网络条件,它有助于正确选择所需的路由协议。

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