Real-Time QoS Optimization for Vehicular Edge Computing With Off-Grid Roadside Units

Abstract

To sustainably provide low-latency communication and edge computing for connected vehicles, a promising solution is using Solar-powered Roadside Units (SRSUs), which consist of small cell base stations and Mobile Edge Computing servers. However, due to the intermittent nature of solar power, SRSUs may suffer from a high risk of power deficiency, which will lead to severe disruption of vehicular edge computing applications. In this paper, we aim to address this challenge of Quality of Service (QoS) loss (i.e., edge computing service outage for vehicle users (VUs)). We formulate a QoS optimization problem for VUs and solve it in two phases: an offline solar energy scheduling phase, and an online user association and SRSU resource allocation phase. We simulate our proposed technique in a dense SRSU network environment with real-world urban vehicular traffic data and solar generation profile. The simulation results show that our proposed approach can significantly reduce QoS loss of vehicular edge computing applications using SRSUs, compared to existing techniques. Further, the results are beneficial to service providers and city planners to identify adequate SRSU configurations for expected solar energy generation and edge computing service demands.