Open Access
ARTICLE
An Energy-Efficient Mobile-Sink Path-Finding Strategy for UAV WSNs
Department of Computer and Communication Technology, Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Perak, 31900, Malaysia
* Corresponding Author: Lyk Yin Tan. Email:
Computers, Materials & Continua 2021, 67(3), 3419-3432. https://doi.org/10.32604/cmc.2021.015402
Received 19 November 2020; Accepted 19 December 2020; Issue published 01 March 2021
Abstract
Data collection using a mobile sink in a Wireless Sensor Network (WSN) has received much attention in recent years owing to its potential to reduce the energy consumption of sensor nodes and thus enhancing the lifetime of the WSN. However, a critical issue of this approach is the latency of data to reach the base station. Although many data collection algorithms have been introduced in the literature to reduce delays in data delivery, their performances are affected by the flight trajectory taken by the mobile sink, which might not be optimized yet. This paper proposes a new path-finding strategy, called Energy-efficiency Path-finding Strategy (EPS) in the Air-Ground Collaborative Wireless Sensor Network (AGCWSN). The proposed approach is able to greatly enhance the efficiency of data collection. The performance of the proposed strategy is simulated and compared with the existing strategies over several parameters. The simulation results show that the mobile sink with EPS can collects data with lower data delivery delay as compared to other existing strategies. The number of data retransmissions between sensor nodes and mobile sink in EPS is also the lowest in EPS among several existing strategies. The data delivery delay is 66% and 120% lower than Rest Center Tractor Scanning (RCTS) and Non-stop Center Tractor Scanning (NCTS) in irregular and grid topology respectively. The data delivery delay is 62% lower than Two Row Scanning (TRS) in grid topology and 120% lower than RkM in irregular topology. The packet loss of EPS-2 is 1.3% lower than RkM.Keywords
Cite This Article
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.