Abstract—Using mobile charging devices to provide
controllable and sustainable energy to Wireless Sensor
Networks (WSN), has become an important topic of current
research. A novel charging strategy based on the mobile device
is proposed to add the net increase in network power. To
improve the charging efficiency and avoid unnecessary
charging, a charging threshold is evaluated and determined. A
Modified Ant Colony Optimization (MACO) is introduced to
minimize the travelling distance of the mobile charging device.
A dynamic state transition rule, which considers the real-time
power of the nodes is developed in MACO to guide the
charging path of the mobile charging device. The sustainability
of the WSN using the proposed charging strategy is also
studied. A WSN model with 50 nodes and one mobile charging
device is used to testify the effectiveness and the efficiency of
the proposed method. The results demonstrate that the
proposed charging strategy can maximize the net increase of
the average power of the WSN with a shorter route in one or
multiple charging tour and ensure the power supply of the
WSN maintaining in a healthy state.
Index Terms—Wireless sensor network, mobile charging,
MACO, sustainability.
The authors are with the School of Mechanical and Electrical Engineering,
China Jiliang University, Hangzhou 310018, China (Corresponding author:
Siguang An; e-mail: mc_y2019@163.com, annsg@126.com,
wangwei@cjlu.edu.cn, lindehui@cjlu.edu.cn, lmzcjn@cjlu.edu.cn,
slh@cjlu.edu.cn).
[PDF]
Cite: Chao Ma, Siguang An, Wei Wang, Dehui Lin, Mei Li, and Lihong Sun, "Wireless Sensor Network Charging Strategy Based on Modified Ant Colony Algorithm," International Journal of Materials, Mechanics and Manufacturing vol. 8, no. 3, pp. 155-161, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (
CC BY 4.0).
![[Click]](http://www.ijmmm.org/img/ijmmm_v7n2_inspec%28IET%29_indexscreenshot.jpg){kind=link}