QoE-based node selection strategy for edge computing enabled Internet-of-Vehicles (EC-IoV)
Yang Cao, Yulong Chen · 2017
With the emergence of computation intensive applications, a huge number of end-user devices are in urgent need of computational capabilities. Up-to-now, conventional cloud-based solutions are challenged by the bottleneck of network bandwidth, high delay and low quality of experience (QoE). In this paper, we illustrate the concept of edge computing enabled Internet-of-Vehicles (EC-IoV), which leverages connected vehicles as the edge computing platform. Then, we design a QoE based node selection (QNS) strategy, through which users can choose a proper edge node from quantities of vehicles to achieve a satisfying QoE on the whole. Simulation results demonstrate the QoE enhancement of QNS when compared with baseline strategies.