Applied Sciences (Apr 2022)
Intelligent Task Offloading in Fog Computing Based Vehicular Networks
Abstract
Connected vehicles in vehicular networks will lead to a smart and autonomous transportation system. These vehicles have a large number of applications that require wireless connectivity by using cellular vehicle-to-everything (C-V2X). The infrastructure of C-V2X comprises multiple roadside units (RSUs) that provide direct connectivity with the on-road vehicles. Vehicular traffic applications are mainly categorized into three major groups such as emergency response traffic, traffic management and infotainment traffic. Vehicles have limited processing capabilities and are unable to process all tasks simultaneously. To process these offloaded tasks in a short time, fog servers are placed near the RSUs. However, it is sometimes not possible for the fog computing server to process all offloaded tasks. In this work, a utility function for the RSU to process these offloaded tasks is designed. In addition, a knapsack-based task scheduling algorithm is proposed to optimally process the offloaded tasks. The results show that the proposed scheme helps fog nodes to optimally scrutinize the high-priority offloaded tasks for task execution resulting in more than 98% of emergency tasks beingprocessed by fog computing nodes.
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