Abstract

The rapid collapse of conventional communication networks during large-scale disasters has often created severe delays in emergency response. Communities have faced life-threatening conditions when the damaged infrastructure restricted timely coordination. This study addressed that challenge by designing an adaptive edge-assisted framework that reduced end-to-end latency during crisis operations. The background of this work focused on how earlier systems relied on centralized cloud servers, which introduced long routing paths and unstable links under stress. Such limitations have often lowered reliability when first responders needed immediate access to situational information. The problem became more critical when dynamic environmental changes forced devices to operate under intermittent connectivity. These disruptions have often prevented smooth message flow across the network. To overcome this gap, the proposed method introduced an integrated architecture that placed intelligence at the edge nodes. The system used a lightweight scheduling module that coordinated the data flow based on link quality and congestion. A context-aware routing unit handled real-time traffic while maintaining continuity for life-saving alerts. The design also used a local caching layer that stored relevant updates during temporary link failures. The evaluation demonstrates that the framework achieves end-to-end delay reduction to 55–67 ms, compared to 105–180 ms for existing methods. The packet delivery ratio reaches 96.5–98.5%, surpassing UAV- assisted relay (85–92%), delay-tolerant networking (75–80%), and fog- based architecture (90–94%). The throughput improves to 9.1–10.2 Mbps, while caching efficiency reaches 92–95%, indicating robust message continuity during temporary link failures. Additionally, energy consumption is reduced to 9.5–10.5 J, reflecting optimized edge processing. These results validate that the framework significantly enhances responsiveness, reliability, and energy efficiency, offering a practical solution for disaster-affected areas.