Collaborative Cloud Computing Based Internet of UAV Things Implementation with Harris Hawks Optimization Algorithm for HetNet in Mountainous Zones

초록

The integration of the Internet of UAV Things (IoUT) with collaborative cloud computing has emerged as a transformative approach to enhancing communication networks, particularly in challenging environments like mountainous zone. These areas pose unique challenges, including signal propagation issues, energy constraints, and the need for seamless coordination among heterogeneous networks (HetNets). Existing models have mainly concentrated on enhancing security and network performance in urban and flat environments; the challenges of mountainous regions have been largely disregarded. Furthermore, the collaborative potential of cloud-based systems for optimizing UAV operations within HetNets has yet to be completely realized. To address these issues, this study proposes a novel collaborative cloud computing-based IoUT framework optimized with the Harris Hawks optimization (HHO) algorithm. The framework is designed to improve UAV communication, resource allocation, and energy efficiency by applying collaborative cloud computing to reduce the computational burden on individual UAVs. Through adaptive fine-tuning of system parameters, the HHO algorithm ensures robust performance under dynamic environmental conditions. Simulation results validate the proposed model, demonstrating significant improvements in coverage, reduced latency, enhanced energy efficiency, and increased resilience to signal degradation. This collaborative framework enables realtime data sharing and decision-making, paving the way for reliable and efficient UAV operations in mountainous zones.

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