代价均衡的无线传感网能量空洞缓解机制研究

发布时间：2018-06-15 11:18

本文选题：无线传感网 + 能量空洞　；参考：《南京邮电大学》2017年硕士论文

【摘要】：在无线传感网中,对于如何有效利用节点的有限能量来最大限度的发挥网络整体功效并延长网络生命周期,始终是其关键问题之一。由于部分节点自身储备的能量过早消耗殆尽,从而导致网络原有覆盖区域的缺失或者节点采集的数据信息无法送达到Sink的“能量空洞”现象。对于“能量空洞”现象的研究已经成为了无线传感网的研究热点。本文分别针对圆形和矩形网络,设计并实现了两类能量空洞缓解方法。具体包括——(1)基于虚拟环的圆形传感网能量空洞缓解方法利用环间节点非均匀分布部署,结合最优父节点选择算法,提出了一种基于相邻环间节点同步工作的能量空洞缓解方法(SNAA)。为降低网络中心附近节点的负载,首先将圆形网络划分为若干等宽的虚拟环,节点在各环内随机部署且各环中的节点数量按照一定比例由外环向内环递增。随后,各节点通过考虑其候选父节点的剩余能量及节点间距来选择最优父节点,并在环间数据收发过程中,进一步实现了节点的休眠调度,降低了处于空闲监听状态的节点的能耗。仿真结果表明,SNAA方法与吴小兵、刘安丰等人提出的方法相比,在能耗均衡方面的性能较优。(2)基于移动Sink的矩形传感网能量空洞缓解方法首先,将矩形网络划分为虚拟栅格以使得节点在各栅格中形成簇状结构。随后,以移动Sink为根节点,以各栅格内的簇头为中间节点或叶节点,建立一棵数据收集树。为降低节点的数据传输能耗,该Sink将分别计算其当前所建立的数据收集树和其可能移动到邻居栅格后所建立的数据收集树的通信代价,从中选择代价最小的树,并移动至该树根所在的栅格,直到其不再移动为止。仿真结果表明,该方法所建立的数据收集树,在多跳传感网络的节能方面表现较为良好,有效缓解了矩形网络中的能量空洞现象。
[Abstract]:In wireless sensor networks, how to use the limited energy of nodes to maximize the effectiveness of the network and extend the network life cycle is always one of the key issues. Due to the premature depletion of the energy stored by some nodes, the lack of the original coverage area of the network or the inability of the data collected by the nodes to reach the "energy hole" phenomenon of the Sink. The study of "energy hole" has become a hotspot in wireless sensor networks. In this paper, two kinds of energy cavity mitigation methods are designed and implemented for circular and rectangular networks. It includes: (1) the energy cavity mitigation method of circular sensor network based on virtual loop is based on the non-uniform distribution of nodes between rings, combined with the optimal parent node selection algorithm. A new energy void mitigation method based on the synchronization of adjacent nodes between rings is presented in this paper. In order to reduce the load of nodes near the center of the network, the circular network is first divided into a number of virtual rings of equal width. The nodes are randomly deployed in each ring and the number of nodes in each ring increases by a certain proportion from the outer loop to the inner ring. Then, each node selects the optimal parent node by considering the residual energy of its candidate parent node and the distance between nodes, and further realizes the sleep scheduling of the nodes in the process of receiving and sending data between rings. The energy consumption of nodes in idle listening state is reduced. The simulation results show that compared with the methods proposed by Wu Xiaobing and Liu Anfeng, the performance of the SNAA method in energy balance is better than that proposed by Wu Xiaobing and Liu Anfeng. The rectangular network is divided into virtual grids so that nodes form cluster structures in each grid. Then, a data collection tree is established with mobile sink as root node and cluster head in each grid as intermediate node or leaf node. In order to reduce the data transmission energy consumption of the node, the sink will calculate the communication cost of the data collection tree currently established by the node and the data collection tree that may be moved to the neighbor grid to select the tree with the least cost. And move to the grid where the root of the tree is located until it no longer moves. The simulation results show that the data collection tree established by this method performs well in energy saving of multi-hop sensor networks and effectively alleviates the phenomenon of energy holes in rectangular networks.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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