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Coverage maximization in mobile Wireless Sensor Networks utilizing immune node deployment algorithm

机译:利用免疫节点部署算法最大化移动无线传感器网络的覆盖范围

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A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors with sensing, computation and wireless communication capabilities. Each sensor generally has the task to monitor, measure ambient conditions, and disseminate the collected data towards a base station. One of the key points in the design stage of a WSN that is related to the sensing attribute is the coverage of the sensing field. The coverage issue in WSNs depends on many factors, such as the network topology, sensor sensing model, and the most important one is the deployment strategy. The sensor nodes can be deployed either deterministically or randomly. Random deployment of the sensor nodes can cause coverage holes formulation; therefore, in most cases, random deployment is not guaranteed to be efficient for achieving the required coverage. In this case, the mobility feature of the nodes can be utilized in order to maximize the coverage. This is Non-deterministic Polynomial-time hard (NP-hard) problem. So in this paper, the Immune Algorithm (IA) is used to relocate the mobile sensor nodes after the initial configuration to maximize the coverage area with the moving dissipated energy minimized. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation. Simulation results show that the proposed algorithm improves the network coverage and the redundant covered area with minimum moving consumption energy.
机译:无线传感器网络(WSN)由具有传感,计算和无线通信功能的空间分布的自主传感器组成。每个传感器通常具有监视,测量环境条件并将收集到的数据分发给基站的任务。 WSN设计阶段中与感应属性相关的关键点之一是感应区域的覆盖范围。 WSN的覆盖范围问题取决于许多因素,例如网络拓扑,传感器感测模型,而最重要的因素是部署策略。传感器节点可以确定性地或随机地部署。传感器节点的随机部署可能会导致覆盖孔的形成;因此,在大多数情况下,不能保证随机部署能有效实现所需的覆盖范围。在这种情况下,可以利用节点的移动性特征以最大化覆盖范围。这是非确定性多项式时间难题(NP-hard)问题。因此,在本文中,将免疫算法(IA)用于在初始配置后重新定位移动传感器节点,以在最大程度地减小移动耗散能量的情况下最大化覆盖范围。使用Matlab仿真将提出的算法的性能与以前的算法进行比较。仿真结果表明,该算法以最小的移动消耗能量提高了网络覆盖范围和冗余覆盖范围。

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