UAVs and VANETs Assisted Task Offloading in the Internet-of-Things

Abstract

The vision of smart cities seeks to revolutionize urban management and improve the quality of life for residents. Within this model, UAVs (Unmanned Aerial Vehicles) play a vital role, using their onboard sensors to collect valuable data and facilitate important services. Yet, challenges such as limited battery capacity and computa tional power can constrain UAV effectiveness, highlighting the importance of robust offloading solutions. To address this, we propose a unique vehicle-assisted computing offloading architec ture tailored for UAVs operating within a smart city. This framework increases of floading efficiency by leveraging the resources of vehicles in motion. Our approach starts with the creation of a UAV offloading model, providing a structured way to choose the best offloading approach. Next, we use a matching process based on both UAV and vehicle preferences (within the VANET system) to identify the ideal vehi cle partners. We model the exchange of computing data between UAVs and vehicles as a strategic bargaining process, aiming to optimize both efficiency and the benefits for all par ties involved. The architecture includes an offloading algorithm designed to guide decision-making for UAVs and vehicles. Finally, comprehensive simulations demon strate the potential of this scheme to conserve resources and enhance the value gained by both UAVs and vehicles. This reinforces the viability of the solution for successful integration within the smart city environment.