Enhancing Network Lifetime and Data Integrity in WSNs via Optimized Mobile Robot Trajectories

Duyên Thi Nguyễn; Minh Xuan Phan; Tien Manh Ngo; Uoc Quang Ngo; Hoc Thai Nguyen

doi:10.18196/jrc.v6i5.26489

Authors

Duyên Thi Nguyễn Vietnam National University of Agriculture
Minh Xuan Phan VNU International School
Tien Manh Ngo Vietnam Academy of Science and Technology https://orcid.org/0000-0002-6690-9714
Uoc Quang Ngo Vietnam National University of Agriculture https://orcid.org/0000-0002-7583-1939
Hoc Thai Nguyen Vietnam National University of Agriculture https://orcid.org/0000-0002-9617-3605

DOI:

https://doi.org/10.18196/jrc.v6i5.26489

Keywords:

WSNs, Energy-Efficient Trajectory Optimization for Mobile Robots in WSNs, Geometric Solution, Network Lifetime, Data Integrity in WSNs

Abstract

Recent research has shown that utilizing mobile robot data collection from sensor nodes is one of the most critical schemes to prolong the network lifetime in wireless sensor networks (WSNs). By overcoming some limitations of traditional methods where sensing data is sent to a static data collection node through multiple routing paths, the mobile data collection robot-based approaches can completely avoid "hotspot" problem, energy-holes issues thereby balancing node energy consumption in the network. Consequently, many ideas and publications on improving network lifetime in WSNs by utilizing mobile data collection robot(s) have been proposed. However, there is little research that has studied the impact of mobile robot trajectory types on network lifetime improvement. Therefore, it becomes very interesting to investigate data collection process of mobile robots in wireless sensor network. In this paper, we proposed a geometric solution to find optimal trajectories of utilized mobile robots (MRs). Our proposed solution consists of four main stages. In the first stage, the number of cluster head nodes is estimated based on the network size and the density of sensor nodes in the WSN. The second stage involves estimating the spatial region that each mobile robot must cover to collect sensed data from all assigned sensor nodes. In the third stage, an optimal trajectory for each mobile robot is determined. In the fourth and final stage, the Network Control Center (NCC) proceeds to assign optimized trajectories to the remaining mobile robots until all cluster head nodes in the network have been visited. The proposed optimal trajectory for the mobile robot is designed not only to ensure timely collection of all sensed data in the field, but also to minimize the energy consumption of sensor nodes, thereby improving the overall network lifetime. A large number of numerical tests were carried out to evaluate the performance of our proposed algorithm. The simulation results demonstrate that our proposed algorithm achieves a 5.4% improvement in network lifetime compared to other traditional algorithms. Nevertheless, the network lifetime improvement remains dependent on several assumptions made in this study. To address this limitation, the discussion section of the paper outlines potential directions for future work aimed at enhancing the practical applicability of the proposed solution.

Author Biographies

Minh Xuan Phan, VNU International School

Minh Xuan PHAN received the B.Sc. and Ph.D. degrees in automatic control from Ilmenau University of Technology, Germany in 1975 and 1989, respectively. She is currently a professor at VNU–International School. Her research interests include optimal and adaptive control, fuzzy logic inference and neural network.

She can be contacted at: minh.phanxuan@hust.edu.vn.

Tien Manh Ngo, Vietnam Academy of Science and Technology

Tien Manh NGO received his B.Sc and Ph.D degrees in Automatic Control at Hanoi University of Science and Technology (HUST) in 2001 and 2014, respectively. His research interests include Process control, adaptive control, fuzzy logic and neural network control, automatic robot control, electro-optical system, image Processing.

He can be contacted at: nmtien@iop.vast.vn

Uoc Quang Ngo, Vietnam National University of Agriculture

Uoc Quang NGO, was born in 1983. He received the MA degree in electrical engineering from the Vietnam National University of Agriculture (VNUA), Vietnam, in 2010. In 2023, he received PhD degree from the Institute for Control Engineering and Automation, Hanoi University of Science and Technology, Hanoi, Vietnam. His research interests include control systems, IoT, robots, and AI applications for smart agriculture.

He can be contacted at: nquoc@vnua.edu.vn.

Hoc Thai Nguyen, Vietnam National University of Agriculture

Hoc Thai NGUYEN received his B.Sc and M.Sc degrees in electrical and electronic engineering from Vietnam National University of Agriculture, Vietnam in 2006 and 2010, respectively. He then received PhD degree in infocommunication technologies and Automation at the Budapest University of Technology and Economics (BME), Hungary in 2018. His research interests include wireless sensor networks, Internet of Robotic Things and Applications of Artificial Intelligence in Precision Agriculture.

He can be contacted at: nguyenthaihoc@vnua.edu.vn; thaihocme@gmail.com.

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