Pricing Model for Dynamic Resource Overbooking in Edge Computing
Zhiqing Tang, Fuming Zhang, Xiaojie Zhou, Weijia Jia, Wei Zhao
Abstract
Edge Computing (EC) with cloud-like Quality of Service (QoS) can find its wide applications in various resource-constrained smart cities where the resource requirements can be different during peak and off-peak periods. During off-peak periods, there are often many resources that have been requested but not used, which can be reused to obtain higher profit. However, to the best of our knowledge, there is no effective pricing model or overbooking mechanism in EC. To fill in this gap, a novel pricing model for dynamic resource overbooking is proposed in this paper, specifically: 1) To meet the needs of different users in EC, methods of on-demand, daily, auction, and the new spot billing are designed, in which resources can be overbooked. 2) An auction approach with pricing rule and winner determination rule is designed for auction billing, which is proved to guarantee individual rationality, computational efficiency, and truthfulness. 3) To make more use of the auction approach to utilize idle resources, a dynamic resource overbooking mechanism is introduced, including a cancellation policy and a resource prediction method. The mechanism is validated with real-world data-trace. Experimental results show that the dynamic resource overbooking mechanism maximizes the profit of edge nodes with a high QoS Satisfaction ratio of on-demand and daily billing.