A Practical Data-Gathering Algorithm for Lossy Wireless Sensor Networks Employing Distributed Data Storage and Compressive Sensing

作     者：Zhang, Ce Li, Ou Liu, Guangyi Li, Mingxuan 

作者机构：Natl Digital Switching Syst Engn & Technol R&D Ct Zhengzhou 450002 Henan Peoples R China 

出 版 物：《SENSORS》 (传感器)

年 卷 期：2018年第18卷第10期

页      面：3221-3221页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

基　　金：National Science and Technology Major Projects of China [2016zx03001010] National Natural Science Foundation of China 

主　　题：WSNs CS distributed data storage packet loss rate energy efficiency 

摘      要：Reliability and energy efficiency are two key considerations when designing a compressive sensing (CS)-based data-gathering scheme. Most researchers assume there is no packets loss, thus, they focus only on reducing the energy consumption in wireless sensor networks (WSNs) while setting reliability concerns aside. To balance the performance-energy trade-off in lossy WSNs, a distributed data storage (DDS) and gathering scheme based on CS (CS-DDSG) is introduced, which combines CS and DDS. CS-DDSG utilizes broadcast properties to resist the impact of packet loss rates. Neighboring nodes receive packets with process constraints imposed to decrease the volume of both transmissions and receptions. The mobile sink randomly queries nodes and constructs a measurement matrix based on received data with the purpose of avoiding measuring the lossy nodes. Additionally, we demonstrate how this measurement matrix satisfies the restricted isometry property. To analyze the efficiency of the proposed scheme, an expression that reflects the total number of transmissions and receptions is formulated via random geometric graph theory. Simulation results indicate that our scheme achieves high precision for unreliable links and reduces the number of transmissions, receptions and fusions. Thus, our proposed CS-DDSG approach effectively balances energy consumption and reconstruction accuracy.