Maximizing data gathering in mobile wireless sensor networks

David Martin Amitu
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引用次数: 3

Abstract

Mobile sensors are expected to play a significant role in the next generation Internet of Things (IoT) networks, with sensors in vehicles, drones, robots and more. These mobile sensors participate in data gathering for various application scenarios. Some applications are information intensive in that huge chunks of data are required in order to make informative decisions. However, mobility in Wireless Sensor Networks greatly limits the amount of data that can be gathered. We therefore propose an approach for maximizing data gathering in mobile Wireless Sensor Networks. The main objective of this approach is to maximize the data gathering capability of the mobile sensor network for information intensive applications using a dual-stage maximization approach which involves maximizing data gathered within each cluster through a proper selection of cluster heads and maximizing data transmitted to the Base station from cluster heads using a near-optimal transmission duration. Simulation results of our proposed approach show significant data gathering performance gains.
在移动无线传感器网络中最大化数据收集
预计移动传感器将在下一代物联网(IoT)网络中发挥重要作用,传感器将应用于车辆、无人机、机器人等。这些移动传感器参与各种应用场景的数据收集。有些应用程序是信息密集型的,因为需要大量的数据来做出信息决策。然而,无线传感器网络的移动性极大地限制了可以收集的数据量。因此,我们提出了一种在移动无线传感器网络中最大化数据收集的方法。该方法的主要目标是使用双阶段最大化方法最大化移动传感器网络的数据收集能力,用于信息密集型应用,该方法包括通过适当选择簇头最大化每个簇内收集的数据,并使用近乎最佳的传输持续时间最大化从簇头传输到基站的数据。仿真结果表明,我们提出的方法显著提高了数据收集性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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