Research on Task-Offloading Delay in the IoV Based on a Queuing Network

In this paper, we address the challenge of task offloading for mobile edge computing in the Internet of Vehicles (IoV). We employ a closed queuing network model to analyze the optimal server load percentage, focusing on the response time of tasks. We evaluate the delay of task offloading by constructing a closed queuing network model and applying the analysis of this network. Additionally, we analyze the system performance by varying the number of vehicles, the number of edge servers, and the edge server load percentage. The results of the study show that there exists an optimal edge server load percentage during task offloading, and this value makes it possible to compute the minimum average response time spent for a task during offloading while ensuring fairness in offloading delays. Increasing the number of edge servers affects the selection of the optimal load percentage, which in turn reduces the minimum response time. Moreover, as the number of vehicles increases, the average response time of tasks in the system increases accordingly. This paper provides a solution for delay-oriented task offloading in the IoV.