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HEPSO: an efficient sensor node redeployment strategy based on hybrid optimization algorithm in UWASN

机译:HEPSO:基于UWASN混合优化算法的高效传感器节点重新部署策略

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摘要

In Underwater Acoustic Sensor Network (UWASN), node redeployment strategy is utilized to handle the reliable network coverage. The sensors deployed in the underwater are used to intellect the area and collected information is moved to the sink node. Node redeployment strategy is essential for the nodes which are placed outside the monitoring area in UWASN. In this paper, the node redeployment strategy is performed based on the hybrid Emperor Penguin Optimization (EPO) algorithm with Particle Search Algorithm (PSO) for better underwater acoustic communication and the proposed method is named as HEPSO. This hybridization is performed to reduce node failure rate and network energy consumption rate by optimally place the sensor nodes in underwater acoustic communication. The stability of the network topology is guaranteed by this algorithm and it enhances the node redeployment strategy by calculating the fitness function for each and every node. The implementation of the proposed algorithm is carried out by the MATLAB platform. The performance parameters like network coverage rate, network connectivity rate, network lifetime, number of nodes outside monitored space and total movement distance of nodes are evaluated and related with current methods like NRBSCT (Node Redeployment Based on Stratified Connected Tree) and MRNR (Moving Redundancy Nodes Redeployment) strategy.
机译:在水下声学传感器网络(UWASN)中,利用节点重新部署策略来处理可靠的网络覆盖范围。部署在水下的传感器用于智能区域,并将收集的信息移动到汇聚节点。节点重新部署策略对于放置在UWASN的监视区域之外的节点至关重要。在本文中,基于对粒子搜索算法(PSO)的混合皇帝企鹅优化(EPO)算法来执行节点重新部署策略,以便更好地水下声学通信,并且所提出的方法被命名为HEPSO。通过最佳地将传感器节点放置在水下声学通信中,执行该杂交以降低节点故障率和网络能耗速率。该算法保证了网络拓扑的稳定性,它通过计算每个节点的适应性函数来增强节点重新部署策略。所提出的算法的实现由Matlab平台执行。评估网络覆盖率,网络连接率,网络生命周期数等的性能参数,并与NRBSCT等当前方法(基于分层连接树)和MRNR(移动冗余)等当前方法进行评估,以及与节点的总移动距离相同的性能参数。节点重新部署)策略。

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