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Abduljabbar Rashid, Sami, Audah, Lukman, Hamdi, Mustafa Maad, Salah Abood, Mohammed, Abbas, Ghassan Raad, Mohammed, Bassim Sayed, Elwi, Taha A., Khan, Salahuddin, Virdee, Bal Singh, Krasniqi, Astrit, Kouhalvandi, Lida and Alibakhshikenari, Mohammad (2025) Delay-minimization and back-off aware Q-learning with advanced bio-inspired CH selection for multi-hop communication in vehicular ad-hoc networks. Radio Science, 60 (6). pp. 1-19. ISSN 1944-799X
The increasing significance of Vehicular Ad-hoc Networks (VANETs) in intelligent transportation systems has introduced challenges related to high mobility, network congestion, and energy efficiency. To address these challenges, this paper proposes a new approach based on Delay-Minimization and Back-Off Aware Q-Learning with Advanced Bio-Inspired Cluster Head (CH) Selection (DBACH) to enhance multi-hop data transmission in VANETs. The DBACH framework is structured around network construction, delay minimization, a back-off Q-learning model, and an improved dragonfly algorithm-based CH selection process. By integrating these mechanisms, the proposed approach effectively minimizes transmission delay, routing overhead, and power consumption, thereby improving Quality of Service (QoS) in VANETs. To validate the performance of DBACH, extensive experiments were conducted, comparing it with existing approaches such as RCDC, DCPA, and WCAM. The simulations were carried out by varying the number of vehicles and their speeds (km/h), analyzing key performance metrics such as energy efficiency, throughput, packet delivery ratio, data loss ratio, computational time, and routing overhead. The results demonstrate that DBACH achieves significant performance gains, with energy efficiency reaching 85 joules, throughput improving to 160–200 Kbps, and an 11–13% increase in packet delivery ratio. Additionally, end-to-end delay is reduced to 60–94 ms, data loss is minimized to 7–15%, and routing overhead is maintained within 170–300 packets. These improvements affirm that DBACH provides high efficiency, greater communication stability, and superior success rates compared to existing methods, making it a promising solution for enhancing reliable and energy-efficient communication in VANETs.
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