Call For Paper Volume: V, Issue: 08 | AUGUST 2026 | International Journal of Advanced Trends in Engineering and Management (IJATEM)
Volume V | Issue 1 | 2026 | Paper ID: IJATEM-V05I01P5

Consumer-Centric Disaster Data Collection in MANET Clouds Using Graph Neural Networks and Particle Swarm Optimization

, K. Eswaramoorthy, Mukela M

In disaster management for Mobile Ad Hoc Networks (MANETs), reliable and efficient data collection is required for timely emergency response. The study introduce a use of Graph Neural Networks (GNN) and Particle Swarm Optimization (PSO) to enhance data communication in disaster-affected areas. PSO is used to optimize relay node selection based on multiple factors like residual energy, connectivity, distance, and traffic load. GNN is employed to analyze the network conditions and to help routing decisions intelligently. The proposed framework executes data collection, duplicate elimination, priority assignment and data fusion to manage emergency information in an efficient manner. Disaster-aware routing improves reliability through adaptive path maintenance and priority-based forwarding. The proposed system is implemented in NS-2 simulator and evaluate effectiveness through various parameters, such as Packet Delivery Ratio (PDR), residual energy, Packet Drop, End- To-End Delay (E2E) and routing overhead. The purpose of the proposed approach is to achieve fast and reliable communication even in dynamic MANET cloud environments.

MANET, Particle Swarm Optimization, Graph Neural Networks.

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