Genetic Algorithm Approach improved by 2D Lifting Scheme for Sensor Node Placement in Optimal Position

T. Ganesan, P. Rajarajeswari
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引用次数: 4

Abstract

In this smart connected world, Sensors are scattered in the environment of interest in order to perform a surveillance monitoring activity for the target operational research. In order to cover the target, sensor node placement plays a crucial role to cover maximum target and minimum node connectivity with limited nodes. Sensor data gathering can be achieved by using important principle node connectivity. Signals in sensor network carry a large amount of data and retaining important information is often more difficult. To overcome this problem we propose a genetic algorithm based node placement the result is improved by wavelets to achieve a maximum coverage and connectivity. The experimental result is carried out to improve the quality of covered data with limited sensor in optimal positions.
基于2D提升方案的遗传算法优化传感器节点位置
在这个智能互联的世界中,传感器分散在感兴趣的环境中,以便为目标运筹学执行监视监测活动。为了覆盖目标,传感器节点的布置起到了至关重要的作用,即在有限节点下覆盖最大目标和最小节点的连通性。传感器数据采集可以通过利用重要的主节点连通性来实现。传感器网络中的信号承载着大量的数据,重要信息的保留往往比较困难。为了克服这一问题,我们提出了一种基于遗传算法的节点放置方法,通过小波对结果进行改进,以达到最大的覆盖和连通性。实验结果表明,在有限的传感器处于最优位置时,覆盖数据的质量得到了提高。
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