Yu Shanen, Liu Shuai, Jiang Peng
College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
Sensors (Basel). 2016 Dec 12;16(12):2103. doi: 10.3390/s16122103.
Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs) usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.
大多数现有的水下无线传感器网络(UWSN)事件覆盖部署算法通常没有考虑到网络通信在三维水下环境中具有非均匀特性。此类部署算法忽略了节点分布在不同深度且数据采集概率不同,从而导致整个网络能耗不均衡,降低网络性能,并致使网络后期运行不佳且不可靠。因此,在本研究中,我们提出了一种基于网络分层的非均匀簇部署算法用于事件覆盖。首先,根据水下网络不同深度通信负载的能耗需求,经过理论分析与推导得出部署节点的期望值以及各层网络的分布密度。随后,基于非均匀簇将网络划分为多层,节点的异构通信半径可提高网络连通率。采用恢复策略平衡簇内节点的能耗,并能高效地重构网络拓扑,这确保了网络在长时间数据采集中具有较高的网络覆盖率和连通率。仿真结果表明,所提算法通过显著减少整个网络节点的盲目移动,在保持高网络覆盖率和连通率的同时,提高了网络可靠性并延长了网络寿命。