Routing selection in mobile ad hoc network using soft computing approaches

Hany Ramadan, B. S. Tawfik, A. Riad
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引用次数: 1

Abstract

Routing in the mobile ad hoc network (MANET) is a challenging task and has received a great amount of attention from researchers. This paper introduces an exact reference routing model to find the shortest path (optimum route). This model is a conventional combinatorial that selects the shortest route from all possible routes. To demonstrate the use of this reference model for comparison a second model is selected which is a modified ant colony optimisation (ACO). The good selection of the heuristic parameters of the ACO model increases its matching degree with the reference one. Therefore, a training pre-processing phase is added to select the best parameters for ACO model. The two models are compared using four different criteria. These criteria are the execution time, energy consumption, the total cost, and the network lifetime. A simulation experiment is performed, and the results show that the modified ant colony algorithm is superior in execution time but consumed more energy than the reference combinatorial and its total cost is greater than or equal to the other one. The lifetime analysis shows that the reference model has better lifetime than the modified ACO model.
基于软计算方法的移动自组网路由选择
移动自组织网络(MANET)中的路由是一项具有挑战性的任务,受到了研究人员的广泛关注。本文介绍了一种精确参考路由模型,用于寻找最短路径(最优路径)。该模型是一个从所有可能的路径中选择最短路径的传统组合模型。为了演示使用该参考模型进行比较,选择了第二个模型,这是一个改进的蚁群优化(ACO)。蚁群算法的启发式参数选择得当,提高了算法与参考算法的匹配程度。因此,增加一个训练预处理阶段,为蚁群算法模型选择最佳参数。这两个模型使用四种不同的标准进行比较。这些标准包括执行时间、能耗、总成本和网络生命周期。仿真实验结果表明,改进蚁群算法在执行时间上优于参考组合算法,但能量消耗较大,总代价大于或等于参考组合算法。寿命分析表明,参考模型的寿命优于改进的蚁群算法模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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