Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks

• Published in: Complexity (New York, N.Y.) Vol. 2021; no. 1
• Main Authors: Chao, Fan, He, Zhiqin, Feng, Renkuan, Wang, Xiao, Chen, Xiangping, Li, Changqi, Yang, Ying
• Format: Journal Article
• Language: English
• Published: Hoboken Hindawi 2021; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Clustering; Communication; Data collection; Energy consumption; Network latency; Optimization; Physical tests; Sensors; Simulation; Unmanned aerial vehicles; Wireless networks; Wireless sensor networks
• DOI: 10.1155/2021/3941074
• ISSN: 1076-2787

Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.