- Research Article
- 10.1109/ojcoms.2026.3663770
Robust Task Offloading in Digital Twin-Enabled UAV-IoT Networks Under Spatial Uncertainty
- Jan 01, 2026
- IEEE Open Journal of the Communications Society
- Muhammad Yahya + 4 more +4
With technological advancements, Unmanned Aerial Vehicles (UAVs) are becoming prominent in next-generation wireless networks because they enable rapid deployment, enhance coverage, and provide advanced services to end users. End users benefit significantly from offloading complex and computationally demanding tasks to flying platforms made possible by UAVs outfitted with edge computing servers. However, attaining optimal and effective network performance depends on proper resource management. The capabilities of next-generation networks are increased through the integration of UAV-assisted Mobile Edge Computing with current wireless infrastructure. In recent era, Internet of Things (IoT) devices are frequently used for real-time data monitoring, gathering, analysis, and transmission for decision-making. This paper presents an optimization problem to increase the number of IoT devices UAVs can serve while minimizing latency and resource costs related to communication, computing, caching, and energy harvesting. We developed a robust offloading strategy that dynamically adapts to IoT spatial perturbations, ensuring efficient workload distribution and minimizing latency. Additionally we integrated Digital Twin technology, allowing thorough network replication and monitoring to analyse latency. A complex mixed-integer nonlinear programming problem has been formulated. We provide a multi-stage offloading mechanism called the Integrality Gap Method with an Interior Point mechanism to tackle this complexity. Simulation findings show that the suggested approach performs better than the straightforward relaxation heuristic technique, confirming its effectiveness.
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