Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks
Autor: | Fan Chao, Zhiqin He, Renkuan Feng, Xiao Wang, Xiangping Chen, Changqi Li, Ying Yang |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: | |
Zdroj: | Complexity, Vol 2021 (2021) |
Druh dokumentu: | article |
ISSN: | 1076-2787 1099-0526 |
DOI: | 10.1155/2021/3941074 |
Popis: | 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. |
Databáze: | Directory of Open Access Journals |
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