Energy-Efficient Framework for Task Caching and Computation Offloading in Multi-Tier Vehicular Edge-Cloud Systems

The proliferation of mobile Internet of Things (IoT) applications like au- tonomous vehicles and augmented reality demands processing power beyond traditional devices. Vehicular Edge-Cloud Computing (VECC) emerges as a solution, leveraging distributed computing resources at the network’s edge (e.g., roadside units) and the cloud for remote task execution. However, energy effi- ciency remains a concern. This paper proposes an energy-efficient framework for VECC. To optimize resource utilization, a caching mechanism stores completed tasks at the edge server for faster retrieval. Additionally, an optimization model minimizes energy consumption while adhering to latency constraints during task offloading and resource allocation. Simulations demonstrate significant energy savings compared to existing benchmarks. This framework addresses both energy efficiency and resource allocation challenges in VECC systems.