UWSNs中面向能耗和延时优化的移动数据收集

为了降低水下无线传感网(UWSN)中数据收集的能耗和保证实时性，提出一种基于压缩感知的移动数据收集方案。以分布式能量均衡非均匀分簇(DEBUC)协议和压缩感知理论为基础，簇内节点依据设计的稀疏测量矩阵决定是否参与压缩采样，并将获得的测量值传输至簇头。然后，通过自主式水下潜器(AUV)的移动来收集各个簇头上的数据到数据中心，该问题被建模为基于信息质量最大化的旅行商问题(TSP)，并提出近似算法进行求解。仿真实验结果表明，相比于已有的水下移动数据收集算法，本文方案在保证数据收集可靠性的同时，缩短了数据收集延时，延长了网络寿命。

Mobile data gathering for energy consumption and delay optimization in Underwater Wireless Sensor Networks

A mobile data collection scheme based on compressive sensing is proposed in order to reduce the energy consumption and ensure real-time performance of data collection in Underwater Wireless Sensor Network(UWSN). Firstly, based on the Distributed Energy-Balanced Unequal Clustering (DEBUC) protocol and compressive sensing theory, cluster nodes decide whether to participate in compressive sampling according to the designed sparse measurement matrix, and transfer the obtained measurement results to the cluster head. Then, the data at cluster head is mobile collected by Autonomous Underwater Vehicle(AUV) to the data center. This problem is modeled as a Traveling Salesman Problem(TSP) based on the maximization of information quality, and an approximate algorithm is proposed to solve this problem. The simulation results show that, compared with the existing underwater data collection algorithms, the proposed scheme effectively reduces the data collection delay and prolongs the lifetime of network, with assuring the reliability of data collection.