声影区影响下的水声传感器网络部署优化算法研究

Research on deployment optimization algorithm for shadow-zone-affected underwater acoustic sensor networks

为提高声影区影响下水声传感器网络的连通性,提升对目标区域的监测质量,提出一种基于深度可调节节点的水声网络部署优化算法(deployment optimization algorithm for shadow-zone-affected underwater acoustic sensor networks,DOASZ)。节点利用来自ARGO(array for real-time geostrophic oceanography)的真实海洋数据估计声影区范围,以最小化节点间信道衰减为目标函数,保证节点移出声影区和控制节点移动能耗为约束条件;基于粒子群算法对节点连通的最优位置进行求解,优化网络部署;设计了基于节点位置、最大移动距离、感知半径的节点移动等待时间和相应的信息传输机制,以保障算法的动态可靠运行。结果表明:算法能在现有部署算法的基础上根据声影区位置进行动态部署优化。当网络中的节点数量为50时,应用DOASZ算法后,随机部署的网络连通性增加了55.9%,基于Voronoi图的深度调节算法部署的网络连通性增加了21.8%,声影区影响下的水声传感器网络连通性明显提升。

To improve the connectivity of underwater acoustic sensor networks under the influence of acoustic shadow zones and enhance the monitoring quality of target areas,DOASZ(deployment optimization algorithm for shadow-zone-affected underwater acoustic sensor networks,DOASZ)is proposed based on adjustable-depth nodes.Nodes use real ocean data from ARGO(array for real-time geostrophic oceanography)to estimate the range of acoustic shadow zones.With minimizing channel attenuation between nodes as the objective function and ensuring nodes movement out of the acoustic shadow zone and controlling nodes movement energy consumption as constraints,the algorithm uses the particle swarm optimization approach to find optimal node positions and the optimize network deployment.To ensure the dynamic and reliable operation of the algorithm,a node movement waiting time and corresponding information transmission mechanism are designed.The node movement waiting time is based on node position,maximum move distance and sensing radius.Simulation results show that the algorithm can dynamically optimize deployment according to the location of acoustic shadow zones based on existing deployment algorithms.When the node number in the network is 50,the network connectivity after applying the DOASZ algorithm is increased by 55.9%for random deployment and by 21.8%for voronoi-based depth adjustment algorithm,the connectivity of underwater acoustic sensor networks affected by acoustic shadow zones is significantly improved.