5G及以后基于物联网传感器网络的移动性辅助自适应聚类层次

B. Dey, Sivaji Bandyopadhyay, Sukumar Nandi
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引用次数: 0

摘要

5G蜂窝网络中用于监控和传感的大规模机器类型通信(mMTC)应用之一是基于物联网(IoT)的无线传感器网络(WSN)。这些网络中节点的电池使用不均匀往往导致网络中产生能量孔或空洞,从而使网络断开。一个有效的解决方案是在整个网络中部署多个移动节点,然而为这些移动节点寻找最优路径是一个NP困难问题。本文提出了MAACH (Mobility Assisted Adaptive Clustering Hierarchy,移动辅助自适应聚类层次结构),这是一种高效的移动辅助聚类和路由框架,适用于5G及以后基于物联网的传感器网络。同时,针对传感节点能量耗散不均匀的问题,提出了一种针对多个移动节点的精确路径优化计算方法。仿真结果表明,该算法能有效地以分布式方式找到多个移动节点的最优轨迹,在多网络部署中,网络稳定周期提高60-70%,网络生存期提高70-90%。
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Mobility Assisted Adaptive Clustering Hierarchy for IoT Based Sensor Networks in 5G and Beyond
One of the massive machine type communication (mMTC) applications for monitoring and sensing in 5G cellular network is the Internet of Things (IoT) based wireless sensor network (WSN). Non uniform battery usage by the nodes in these networks often results in creating energy holes or voids in the network making the network disconnected. An effective solution is to deploy multiple mobile nodes throughout the network, however finding optimal path for these mobile nodes is reported to be an NP hard problem. This paper proposes MAACH (Mobility Assisted Adaptive Clustering Hierarchy), an efficient mobility assisted clustering and routing framework for IoT based sensor network in 5G and beyond. Also, an elaborate method to calculate the exact path optimally for multiple mobile nodes is presented to alleviate non uniform energy dissipation of the sensing nodes. Simulation results show that our algorithm effectively finds the optimal trajectory of multiple mobile nodes in a distribute manner and also improves network stability period by 60-70% and the network lifetime by 70-90% across multiple network deployments.
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