Abstract:
As Internet of things (IoT) technologies advance at a rapid pace, the deployment of sensor-equipped mobile vehicles in smart environments has become widespread. However, these vehicles encounter constraints in computational strength, storage capability and battery longevity, which hinder their ability to independently process all tasks locally. Furthermore, the presence of deficient network connectivity in specific regions poses a significant challenge to the seamless operation of Internet of Vehicles (IoV) systems. Unmanned aerial vehicles (UAVs), known for their manageable mobility and adaptability, have emerged as a prospective solution to facilitate communication in such network-challenged areas. In our Research, we present a computational framework harnessing the potential of UAVs to assist mobile vehicles operating in regions marked by inadequate network connectivity. We introduce two distinct clustering algorithms, namely the Centralized-based Algorithm and Max Connect UAV, designed to enable mobile vehicles to offload computation to nearby UAVs. These algorithms empower mobile vehicles to access nearby computational resources, thereby enhancing their performance, especially for time-sensitive applications. Our methodology effectively addresses the complexities associated with delay-sensitive applications and ensures network cover age in challenging areas. We perform simulation experiments to affirm the effectiveness of our suggested method, employing both the Centralized-based Algorithm and the Max Connect UAV algorithm. The proposed solution provides an architectural framework, enables algorithmic implementation, and demonstrate experimental validation that can also guide emerging and futuristic research on resource provisioning in ad-hoc IoV systems.
