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A New Approach in Energy Consumption Based on Genetic Algorithm and Fuzzy Logic for WSN

机译:基于遗传算法和模糊逻辑的无线传感器网络能耗新方法

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Although the sensor node is tiny, it covers large areas by connecting these nodes together wirelessly, it called wireless sensor network (WSN). WSNs are one of the common things that still evolving very fast nowadays. Routing protocols challenge the energy consumption of wireless sensor networks. In this paper, we proposed a new Fuzzy Logic and Genetic Algorithm based protocol (FL-GA) for WSNs, as follows, we used the fuzzy logic Mamdani method for finding the best cluster heads. We used two inputs for fuzzy, energy and distance, we used the Genetic Algorithm for optimization. Taking into account variable parameters, the choice of cluster heads will be more efficient and the cluster forming will be more accurate, all the nodes will almost die at the same time. One of the classic routing protocols is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. We compared our protocol to the LEACH protocol. Our network nods, still alive much more than the LEACH protocol nodes. The proposed method is more efficient in extending the network lifetime and maximizing the total number of data packets received in the sink.
机译:尽管传感器节点很小,但通过将这些节点无线连接在一起可以覆盖较大的区域,这称为无线传感器网络(WSN)。 WSN是当今仍在快速发展中的常见事物之一。路由协议挑战了无线传感器网络的能耗。在本文中,我们提出了一种新的基于WSN的基于模糊逻辑和遗传算法的协议(FL-GA),如下所示,我们使用模糊逻辑Mamdani方法来寻找最佳的簇头。我们使用了两个输入来表示模糊,能量和距离,并使用了遗传算法进行了优化。考虑到可变参数,簇头的选择将更加有效,簇的形成将更加准确,所有节点几乎都将同时死亡。经典路由协议之一是低能耗自适应群集层次结构(LEACH)协议。我们将协议与LEACH协议进行了比较。我们的网络点头,仍然比LEACH协议节点还活着。所提出的方法在延长网络寿命和最大化接收器中接收到的数据包总数方面更有效。

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