Sustainable Vehicular Edge Computing Using Local and Solar-Powered Roadside Unit Resources

In this paper, we explore a sustainable solution to growing vehicular computing and communication needs by utilizing edge computing and communication resources of a network of Solar-powered Roadside Units (SRSUs), along with any vehicular computing resources available. The solution ensures no additional grid energy expended while minimizing any QoS loss for the vehicle users (VUs). An SRSU consists of a small cell base station (SBS) and a road-edge computing (REC) node, is powered by a low-cost solar system. VUs can offload their vehicular application tasks to SRSUs to receive high throughput and low latency services. However, the limited capacity of solar energy, REC computing, and bandwidth resources may cause service disruption and affect the Quality of Service (QoS) that VUs receive. To minimize such QoS loss, we formulate a dynamic offloading QoS loss minimization problem, where the different subtasks of a VU application are optimally executed either locally using the VU computing resource or remotely using the REC resource, considering the energy, computing and bandwidth constraints of the SRSU network. We then propose to solve it by a heuristic algorithm which jointly makes the optimal user association, subtask offloading, and SRSU resource allocation decisions. To evaluate the proposed algorithm, we build a simulation framework consisting of a dense SRSU network using real-world solar energy generation and urban vehicular traffic data. The simulation results show that our proposed approach can significantly reduce QoS loss compared to other best effort strategies.