TY - GEN
T1 - A Bio-Inspired Metaheuristics Algorithm for Reduction of Coverage Holes in Optimizing the Performance of Next Generation Wireless Network (NGWN)
AU - Ajibade, Samuel Soma M.
AU - Abdul Majeed, Anwar P.P.
AU - Oyebode, Oluwadare Joshua
AU - Jasser, Muhammed Basheer
AU - Ajayi, Babatunde Adedotun
AU - Alebiosu, David Olayemi
AU - Luo, Yang
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - While Next Generation Wireless Networks are widely used, controlling them can be challenging regardless of whether a network is fully connected, there may be coverage gaps. In this study, we provide a technique for placing nodes in a wireless network while making sure that there is a minimum coverage hole in the network coverage area. We use the firefly algorithm to close the coverage gap in order to increase connectivity. The Firefly algorithm provides a novel solution for overcoming the drawbacks of traditional overburden hole detection techniques, such as downtime, low accuracy, and high operating costs, by installing sensor nodes in the appropriate locations and scheduling those network devices. The algorithm looks for the best locations where the NGWN sensor may be placed inside the designated zone in order to reduce the coverage hole area. The algorithm will treat randomly generated solutions as fireflies, and it will determine how bright they are based on how well they perform in terms of the goal function. Simulation results show that the proposed method decreases the covering hole area by 96%. The provided approach was suitable for NGWN since it reduced computation time.
AB - While Next Generation Wireless Networks are widely used, controlling them can be challenging regardless of whether a network is fully connected, there may be coverage gaps. In this study, we provide a technique for placing nodes in a wireless network while making sure that there is a minimum coverage hole in the network coverage area. We use the firefly algorithm to close the coverage gap in order to increase connectivity. The Firefly algorithm provides a novel solution for overcoming the drawbacks of traditional overburden hole detection techniques, such as downtime, low accuracy, and high operating costs, by installing sensor nodes in the appropriate locations and scheduling those network devices. The algorithm looks for the best locations where the NGWN sensor may be placed inside the designated zone in order to reduce the coverage hole area. The algorithm will treat randomly generated solutions as fireflies, and it will determine how bright they are based on how well they perform in terms of the goal function. Simulation results show that the proposed method decreases the covering hole area by 96%. The provided approach was suitable for NGWN since it reduced computation time.
KW - Firefly Algorithm
KW - Fitness function
KW - Network coverage hole
KW - Next Generation Wireless Networks (NGWN)
UR - http://www.scopus.com/inward/record.url?scp=105002719607&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-3949-6_4
DO - 10.1007/978-981-96-3949-6_4
M3 - Conference Proceeding
AN - SCOPUS:105002719607
SN - 9789819639489
T3 - Lecture Notes in Networks and Systems
SP - 41
EP - 60
BT - Selected Proceedings from the 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024 - Advances in Intelligent Manufacturing and Robotics
A2 - Chen, Wei
A2 - Ping Tan, Andrew Huey
A2 - Luo, Yang
A2 - Huang, Long
A2 - Zhu, Yuyi
A2 - PP Abdul Majeed, Anwar
A2 - Zhang, Fan
A2 - Yan, Yuyao
A2 - Liu, Chenguang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024
Y2 - 22 August 2024 through 23 August 2024
ER -