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GOM: New genetic optimizing model for broadcasting tree in MANET

机译:GOM:MANET中广播树的新遗传优化模型

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Data broadcasting in a mobile ad-hoc network (MANET) is the main method of information dissemination in many applications, in particular for sending critical information to all hosts. Finding an optimal broadcast tree in such networks is a challenging task due to the broadcast storm problem. The aim of this work is to propose a new genetic model using a fitness function with the primary goal of finding an optimal broadcast tree. Our new method, called Genetic Optimisation Model (GOM) alleviates the broadcast storm problem to a great extent as the experimental simulations result in efficient broadcast tree with minimal flood and minimal hops. The result of this model also shows that it has the ability to give different optimal solutions according to the nature of the network.
机译:移动自组织网络(MANET)中的数据广播是许多应用程序中信息分发的主要方法,特别是向所有主机发送关键信息时。由于广播风暴问题,在这样的网络中寻找最佳的广播树是一项具有挑战性的任务。这项工作的目的是提出一个使用适应度函数的新遗传模型,其主要目的是找到最佳的广播树。我们的称为遗传优化模型(GOM)的新方法在很大程度上缓解了广播风暴问题,因为实验模拟可生成具有最小泛洪和最小跳数的有效广播树。该模型的结果还表明,它具有根据网络的性质给出不同的最佳解决方案的能力。

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