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An Ant Colony System Based Energy Prediction Routing Algorithms for Wireless Sensor Networks

机译:基于蚁群系统的无线传感器网络能量预测路由算法

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Routing algorithms play important roles in wireless sensor networks (WSNs). Usually, nodes in a WSN run on battery with limited power. Hence, routing with efficient power consumption is becoming a critical issue for WSNs. In this paper, a routing algorithm, referred to as Energy Prediction and Ant Colony Optimization Routing (EPACOR), is proposed. In the EPACOR, when a node needs to deliver data to the sink, ant colony systems are used to establish the route with optimal or sub-optimal power consumption, and meanwhile, learning mechanism is embedded to predict the energy consumption of neighboring nodes when the node chooses a neighboring node added to the route. The EPACOR is compared both with the MST (Minimal Spanning Tree)-based routing algorithm following the Prim algorithm and with the Least Energy Tree (LET)-based routing algorithm following the Dijkstra algorithm. Numeric experiment shows that the EPACOR has the best network lifetime among the three while keeping energy consumption in low level.
机译:路由算法在无线传感器网络(WSN)中起着重要作用。通常,WSN中的节点使用电量有限的电池供电。因此,具有高效功耗的路由已成为WSN的关键问题。本文提出了一种路由算法,称为能量预测和蚁群优化路由(EPACOR)。在EPACOR中,当一个节点需要将数据传递到接收器时,使用蚁群系统来建立具有最佳或次佳功耗的路由,同时,嵌入了学习机制来预测相邻节点的能耗。节点选择添加到路由的邻居节点。将EPACOR与基于Prim算法的基于MST(最小生成树)的路由算法以及与基于Dijkstra算法的基于最小能量树(LET)的路由算法进行比较。数值实验表明,EPACOR具有三者中最长的网络寿命,同时将能耗保持在较低水平。

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