Call For Paper Volume: V, Issue: 08 | AUGUST 2026 | International Journal of Advanced Trends in Engineering and Management (IJATEM)
Volume V | Issue 5 | 2026 | Paper ID: IJATEM-V05I05P4

Intelligent Energy-Efficient MANET Clustering Using Artificial Rabbits Optimization and Graph Transformer Network

, E. Immanuvel Bright

Routing challenges in Mobile Ad Hoc Networks (MANETs) are caused by node mobility, limited energy, unstable links and congestion. This work proposes an intelligent routing framework based on ARO-GTN for reliable and energy-efficient communication. Network parameters, such as residual energy, node degree, neighbour distance, mobility, and link quality are collected to characterize the network conditions. The Artificial Rabbits Optimization (ARO) algorithm selects the best cluster heads and creates stable clusters by efficiently exploring and exploiting. Then a Graph Transformer Network (GTN) is applied to model network relationships and predict suitable routing paths using attention based learning. The proposed routing mechanism provides energy aware path selection, congestion avoidance and efficient packet forwarding. The simulation results show that the proposed ARO-GTN allows routing based on energy aware and congestion avoidance. It achieves 83 kbps throughput, 60 J energy consumption, 83% PDR, 60 ms delay and 83 s network lifetime at 100 nodes, showing better network performance.

MANET, ARO, GTN, Intelligent Routing, Cluster Head Selection.

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