Edge Servers on Wheels: Deployment and Route Planning of Mobile Servers for Internet of Vehicles

The rapid development of the Internet of Vehicles (IoV) has boosted the prosperity of various on-vehicle applications, e.g., route guidance, speed advisory, and autonomous driving. These applications call for computation offloading due to limited resources of the users, where edge computing becomes a promising solution. However, it remains an open problem how the user dynamics can be handled by deploying mobile edge servers on service vehicles. To this end, this paper proposes a mobile edge computing deployment scheme to fulfill computation offloading using service vehicles. We first build a mathematical model to characterize the deployment cost of multiple cruising routes of the mobile servers and their bases. Next, we design heuristic algorithms to obtain the solutions based on Adelson-Velsky and Landis (AVL)-tree, Gaussian Mixture Model and Simulated Annealing (GMM-SA). The AVL algorithm is used to partition the map into regions and place bases, and the GMM-SA-based algorithm is designed to find the best routes within each region. Experimental results demonstrate that our proposed mobile server deployment scheme achieves the best performance compared with other popular methods in terms of computation resource utilization and travelling distance of the mobile servers.

I. Introduction

With the continuous development of the Internet of Vehicles (IoV), novel applications have emerged which require low-latency computation, ultra-wide bandwidth transmission, and real-time user interaction [1]–[3]. Edge computing has become the best choice to meet the requirements of the IoV as it places computing resources close to the end users, i.e., vehicles.