A Mobile-assisted Edge Computing Framework for Emerging IoT Applications

Abstract

Edge computing (EC) is a promising paradigm for providing ultra-low latency experience for IoT applications at the network edge, through pre-caching required services in fixed edge nodes. However, the supply-demand mismatch can arise while meeting the peak period of some specific service requests. The mismatch between capacity provision and user demands can be fatal to the delay-sensitive user requests of emerging IoT applications and will be further exacerbated due to the long service provisioning cycle. To tackle this problem, we propose the mobile-assisted edge computing framework to improve the QoS of fixed edge nodes by exploiting mobile edge nodes. Furthermore, we devise a CRI (Credible, Reciprocal, and Incentive) auction mechanism to stimulate mobile edge nodes to participate in the services for user requests. The advantages of our mobile-assisted edge computing framework include higher task completion rate, profit maximization, and computational efficiency. Meanwhile, the theoretical analysis and experimental results guarantee the desirable economic properties of our CRI auction mechanism.