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Article

Extending WSN Lifetime via Optimized Mobile Sink Trajectories: Linear Programming and Cuckoo Search Approaches with Overhearing-Aware Energy Models

by
Ghada Turki Al-Mamari
1,*,
Fatma Bouabdallah
2 and
Asma Cherif
1,3
1
Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
2
School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK
3
Center of Excellence in Smart Environment Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia
*
Author to whom correspondence should be addressed.
Submission received: 5 May 2025 / Revised: 31 August 2025 / Accepted: 4 September 2025 / Published: 14 September 2025

Abstract

Maximizing the lifetimes of Wireless Sensor Networks (WSNs) is a prominent area of research. The energy hole problem is a major cause of network shutdown, where nodes within the Sink coverage deplete their energy faster due to the high energy cost of forwarding data from distant nodes to the Sink. Several research works have proposed solutions to address this issue, including the use of a mobile Sink to balance energy consumption throughout the network. However, most Sink mobility models overlook the energy consumption caused by overhearing, which is a critical factor in WSNs. In this paper, we introduce Linear Programming (LP) and Cuckoo Search (CS) metaheuristic optimization-based solutions to maximize the lifetime of WSNs by determining the optimal Sink sojourn points and associated durations. The proposed approaches consider the energy consumption levels of both reception and transmission, in addition to accounting for overhearing as an additional source of energy consumption. This allows for a comparison between the LP and CS solutions in terms of their effectiveness. To further enhance our solution, we apply the Travel Salesman Problem (TSP) to find the shortest path between the Sink sojourn points. By incorporating the TSP, we can optimize the routing path for the mobile Sink, thereby minimizing energy consumption and maximizing network lifetime. Test results demonstrate that the LP solution provides more accurate Sink sojourn times and locations, while the CS solution is faster, particularly for large WSNs. Moreover, our findings indicate that overlooking overhearing leads to a 48% decrease in WSN lifetime, making it essential to consider this factor if one is to achieve realistic results.
Keywords: wireless sensor networks; mobile Sink; energy hole problem; linear programming; artificial intelligence wireless sensor networks; mobile Sink; energy hole problem; linear programming; artificial intelligence

Share and Cite

MDPI and ACS Style

Al-Mamari, G.T.; Bouabdallah, F.; Cherif, A. Extending WSN Lifetime via Optimized Mobile Sink Trajectories: Linear Programming and Cuckoo Search Approaches with Overhearing-Aware Energy Models. IoT 2025, 6, 54. https://doi.org/10.3390/iot6030054

AMA Style

Al-Mamari GT, Bouabdallah F, Cherif A. Extending WSN Lifetime via Optimized Mobile Sink Trajectories: Linear Programming and Cuckoo Search Approaches with Overhearing-Aware Energy Models. IoT. 2025; 6(3):54. https://doi.org/10.3390/iot6030054

Chicago/Turabian Style

Al-Mamari, Ghada Turki, Fatma Bouabdallah, and Asma Cherif. 2025. "Extending WSN Lifetime via Optimized Mobile Sink Trajectories: Linear Programming and Cuckoo Search Approaches with Overhearing-Aware Energy Models" IoT 6, no. 3: 54. https://doi.org/10.3390/iot6030054

APA Style

Al-Mamari, G. T., Bouabdallah, F., & Cherif, A. (2025). Extending WSN Lifetime via Optimized Mobile Sink Trajectories: Linear Programming and Cuckoo Search Approaches with Overhearing-Aware Energy Models. IoT, 6(3), 54. https://doi.org/10.3390/iot6030054

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