Hyper-heuristic driven sustainable wireless networks for crisis-resilient communication systems

Introduction Communication infrastructures are often severely disrupted during natural disasters, armed conflicts, and large-scale humanitarian crises, hindering coordination among emergency responders and affected populations. Rapidly deployable wireless communication systems, including mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs), offer a viable solution for restoring connectivity in such environments. However, these networks face significant challenges, including dynamic topology changes, limited energy resources, unreliable communication links, and fluctuating traffic demands. Therefore, adaptive and sustainable communication management mechanisms are required to ensure resilient network performance under crisis conditions. Methods This study proposes a hyper-heuristic-driven framework for sustainable and crisis-resilient wireless communication systems. The framework employs a high-level hyper-heuristic controller that dynamically selects appropriate low-level communication heuristics from a heterogeneous pool comprising constructive, improvement, perturbation, and reconstructive strategies. A multi-objective optimization model is formulated to simultaneously minimize energy consumption, communication delay, and packet loss while maximizing network reliability. The heuristic selection process is guided by real-time network state indicators, including residual node energy, link quality, congestion level, and node density. The proposed framework is evaluated through extensive simulations conducted in the NS-3 network simulator under realistic disaster-response scenarios. Results Simulation results demonstrate that the proposed hyper-heuristic framework consistently outperforms conventional routing and communication strategies. Specifically, the approach increases network lifetime by up to 15%, improves packet delivery ratio by approximately 6‐10%, and reduces end-to-end communication delay by nearly 20%. Furthermore, significant improvements in overall energy efficiency are observed, contributing to prolonged network operation in resource-constrained environments. Discussion The findings indicate that hyper-heuristic optimization provides an effective mechanism for adaptive network management in rapidly changing crisis environments. By dynamically selecting communication strategies according to current network conditions, the framework enhances both resilience and sustainability while maintaining high communication performance. The proposed approach offers a practical and scalable solution for emergency response networks, highlighting the potential of hyper-heuristic methodologies to support reliable and energy-efficient wireless communications during disaster recovery and humanitarian operations.