Open Access

ARTICLE

Optimal Coverage Multi-Path Scheduling Scheme with Multiple Mobile Sinks for WSNs

by Jin Wang, Yu Gao, Chang Zhou, R. Simon Sherratt, Lei Wang

1 School of Computer & Communication Engineering, Changsha University of Science & Technology, Changsha, 410114, China.
2 School of Information Engineering, Yangzhou University, Yangzhou, 225009, China.
3 School of Information Science and Engineering, Fujian University of Technology, Fuzhou, 350000, China.
4 Department of Biomedical Engineering, University of Reading, Berkshire RG6 6AY, UK.
5 School of Civil Engineering, Changsha University of Science & Technology, Changsha, 410114, China.

* Corresponding Author: Lei Wang. Email: .

Computers, Materials & Continua 2020, 62(2), 695-711. https://doi.org/10.32604/cmc.2020.08674

Abstract

Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the ‘hot spots’ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy and coverage rate etc., it is still very important to schedule a reasonable moving trajectory for the mobile sink. In this paper, a novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs. An improved particle swarm optimization (PSO) combined with mutation operator is introduced to search the parking positions with optimal coverage rate. Then the genetic algorithm (GA) is adopted to schedule the moving trajectory for multiple mobile sinks. Extensive simulations are performed to validate the performance of our proposed method.

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Citations