UAV-Enabled IoT: Cascading Failure Model and Topology-Control-Based Recovery Scheme
Le Zhang, Ye Du, Jinqi Xu, Xiaolong Wang
Abstract
The emergence of unmanned aerial vehicle (UAV)-enabled Internet of Things (IoT) represents a new paradigm of intelligent monitoring that transcends geographical limitations. However, UAVs are highly sensitive to disruptive factors, and their failure can easily trigger cascading failures due to a surge in traffic. To address this, this article proposes a cascading failure model to help understand cascading risks, incorporating the unique online and offline modes of UAVs. For the issue of IoT devices not being fully covered after a cascading failure, a topology-control-based recovery scheme is proposed. Surviving UAVs are divided into two categories, where backbone UAVs (BUAVs) hover at specific positions to form a reliable backbone network spanning the service area, and cruising UAVs patrol nearby to achieve extensive coverage. To provide a solution, the optimization model is transformed into two stages, and approximate algorithms are developed separately. The improved combination of cuckoo search and a density-based clustering algorithm is employed to determine the positions for BUAVs. Meanwhile, a multistep approach utilizing the nondominated sorting genetic algorithm II is introduced to optimize the cruising paths of UAVs. Case study shows that the proposed cascading failure model is reasonable; the proposed recovery scheme can achieve up to 91% coverage, with most IoT devices covered by cruising UAVs maintaining more than half of their service time; the recovered network can still maintain 50% of IoT devices within coverage under up to 20% link failure. These findings offer network managers practical insights for enhancing network resilience.