能量感知的水下传感器网络水压路由算法

发布时间：2018-06-15 15:36

本文选题：水下无线传感器网络 + 能量感知　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：无线传感器网络(Wireless Senior Network,WSN)经过多年的发展,形成了较为完善的理论体系,这些极大的方便了人们对地区的监测和对环境的感知。随着海洋资源开发、海洋环境监测、辅助导航、灾难预防等方面日益受到重视,无线传感器网络正被应用到水下环境当中。由于水下无线传感器网络(Underwater Wireless Senior Network,UWSN)和传统的陆地无线传感器网络中信号传输的介质和通信方式的不同,陆地传感器网络中的路由协议不能直接应用在水下环境。本文改进了一种基于节点深度信息的UWSN路由算法,该算法适用于对相对封闭(比如湖泊、水库)并需要进行长期监测的场景。改进算法通过节点上附加的廉价水压传感器来获取节点的深度信息,一个节点的路由信息包含两项:自身的转发方向、下一跳转发方向。转发数据时,根据节点的路由方向信息选择备选下一跳节点,然后根据节点的优先级来将备选节点分成内部不含隐藏终端的集合,在转发的数据包中会包含节点集合的信息,优先级高的节点会获得优先转发数据的机会。节点的优先级由其相对于发送节点的深度差,节点剩余能量以及节点间的距离共同决定。算法对于原算法的改进之处在于:第一,在下一跳的选择过程中引入节点剩余能量作为参考因素,让处在相近深度上的节点中,能量高的有着更高的可能性成为下一跳,有利于网络中节点能量的均衡,防止区域内节点过早稀疏而降低网络中的连通性。第二,提出一种新的信标增强周期的确定方法,此方法能够自适应水流的变化,不需要知道节点的速度。由于水下情况复杂,不同的节点的移动速度可能是不一样的,而且节点在水下没有定位系统辅助的情况下其移动速度也难以确定。新方法通过水面汇聚节点最近一轮数据采集阶段所收到的节点数和估计的能和水面节点通信的剩余节点数来决定信标增强的时机而无需参考节点速度。第三,由于节点的移动,节点到水面的链路可能会因临时中断而错过信标增强阶段的路由建立。改进算法在向水面转发的感知数据包中加入必要的信息,来帮助那些路由过期的节点重构路由。本文用仿真软件OMNeT++对两种算法进行仿真分析,在近似的数据投递率下,改进算法的路由开销小于原算法,在合适的水流速度和节点密度下可以比原算法小5%~15%,在网络生存周期方面,改进算法相对于原算法有10%~30%的提升。
[Abstract]:After years of development, Wireless Senior Network WSNs have formed a relatively perfect theoretical system, which greatly facilitates the monitoring of the region and the perception of the environment. With the development of marine resources, marine environmental monitoring, auxiliary navigation, disaster prevention and other aspects of increasing attention, wireless sensor networks are being applied to underwater environment. Due to the difference between underwater Wireless Senior Network (UWSN) and traditional terrestrial wireless sensor networks (WSNs), the routing protocols in terrestrial wireless sensor networks can not be directly applied in underwater environments. In this paper, an improved UWSN routing algorithm based on node depth information is proposed. This algorithm is suitable for scenarios with relatively closed (such as lakes, reservoirs) and needs to be monitored for a long time. The improved algorithm obtains the depth information of a node by adding a cheap water pressure sensor to the node. The routing information of a node contains two items: its forwarding direction and the next hop forwarding direction. When forwarding the data, the next hop node is selected according to the routing direction information of the node, and then the alternative node is divided into a set without hidden terminals according to the priority of the node, and the information of the node collection is included in the transmitted data packet. High priority nodes are given the opportunity to forward data first. The priority of the node is determined by its depth difference relative to the sending node, the residual energy of the node and the distance between the nodes. The improvement of the original algorithm is as follows: first, in the selection of the next jump, the residual energy of the node is introduced as a reference factor, so that the node with high energy is more likely to be the next jump in the near depth. It is beneficial to the equalization of node energy in the network, prevents the nodes in the region from becoming sparse prematurely and reduces the connectivity in the network. Secondly, a new method for determining the period of beacon enhancement is proposed. This method can adapt to the change of water flow without knowing the speed of the node. Because of the complexity of underwater situation, the moving speed of different nodes may be different, and it is difficult to determine the moving speed of nodes without the assistance of underwater positioning system. The new method determines the time of beacons enhancement by the number of nodes received in the most recent round of data acquisition and the estimated number of remaining nodes that can communicate with the surface nodes without reference to the node speed. Third, because of the node movement, the link between the node and the water surface may miss the route establishment of the beacon enhancement phase due to the temporary interruption. The improved algorithm adds the necessary information to the perceptual packets forwarded to the water to help those nodes whose routing is expired to reconstruct the routing. In this paper, we use OMNeT to simulate the two algorithms. Under the approximate data delivery rate, the routing overhead of the improved algorithm is smaller than that of the original algorithm. Under the appropriate flow velocity and node density, the proposed algorithm can be 5 / 15 smaller than the original algorithm. In the network lifetime, the improved algorithm has a 10% or 30% increase compared with the original algorithm.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN929.3

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