Abstract
Edge computing has been proved an efficient approach to provisioning
computation offloading service to vehicles on road through Road-Side
Units (RSUs). However, the traffic volume on road is highly dynamic,
while RSU-based edge servers are static in terms of geographical
location and computation capacity. To address this problem, this paper
proposes a mobile edge server placement strategy using cruising UAVs
along the roads based on the genetic algorithm. We first build a
mathematical model to characterize the deployment cost of these
UAV-mounted servers and their routes. Next, we design a heuristic
UAV-mounted edge server deployment scheme based on K-medoid clustering
and genetic algorithms. Experimental results verify that our proposed
UAV deployment scheme satisfies the offloading demand of IoV nodes while
reducing the total deployment cost by 17.05% to 48.94% compared with
existing popular approaches.