Location-Aware Reliable Task Cooperative-Computation Scheme Under Fog Computing-Based IoVs

Although many existing schemes were proposed to solve the time delay, energy consumption and system architecture issues of task offloading in internet of vehicles (IoVs), few task offloading schemes focus on the location and mobility of vehicle nodes, the reliability of vehicle nodes and communication links, and the workload of fog servers. In this paper, we propose a location-aware reliable task cooperative-computation scheme under fog computing-based IoVs. In comparison to many existing vehicular cooperative computing schemes, our scheme introduces a dual-layer (single-hop and multi-hop) cooperative vehicle assessment and selection mechanism based on the location-aware principle (such as proximity). The proposed mechanism involves a detailed evaluation for cooperative vehicles from three perspectives: the reliability of cooperative vehicle nodes, the reliability of communication links, and the availability of idle computing resources. The comprehensive evaluation is designed to further facilitate the task allocation between the required tasks and the cooperative vehicles. Under the condition of meeting task requirements, the fog server can select closer (single-hop), more reliable vehicles with greater available computing resources to accomplish related sub-tasks for customer vehicles. Additionally, we further propose an enhanced Hungarian algorithm for task allocation among required sub-tasks and selected cooperative vehicles, which can effectively assign corresponding sub-tasks to suitable cooperative vehicles to reduce the fragmentation of vehicular resources and enhance the utilization of vehicular resources. Experimental results demonstrate the effectiveness of our location-aware reliable task cooperative-computation scheme under fog computing-based IoVs.