Service Pricing and Selection for IoT Applications Offloading in the Multi-Mobile Edge Computing Systems

Abstract

With the technologies in Internet of Things (IoT) developing rapidly, various kinds of IoT devices are connected over the Internet. Therefore, how to meet the requirements of the executing IoT applications is becoming a critical issue. Generally speaking, offloading the IoT applications to the public cloud is an efficient approach to process them. However, as there is a long distance from the IoT devices to the remote public cloud, transmission delay will be caused. Mobile edge computing (MEC) provides an effective solution to this issue since IoT devices are near to the servers in the MEC systems. Pricing and load balancing are two important factors for cloud service provision. Pricing provides an effective approach for cloud service provision, and load balancing is an important factor and it is fully considered when cloud users select a edge cloud service provider (ESP) as it has a direct relation with the quality of cloud service. In multi-cloud systems, a cloud service broker (CSB) reserves cloud resources from multiple CSPs to provision cloud services to users. While previous works have put a lot of attention on IoT applications offloading to the MEC, many of them only considered the single cloud, ignoring the multi-MEC scenario. In this paper, we investigate service pricing and selection for IoT applications offloading in a multi-MEC system consisting multiple of ESPs. Specifically, we take load balancing into account. The problem of pricing and selection is formulated as a Stakelberg game, where CSB firstly sets service price and load balancing strategies for the cloud services trying to get its maximized revenue. Then, IoT users make their decisions on which ESP they select service from. By making use of the backward induction approach, the optimal solutions are derived. The proposed scheme of this paper is verified through simulation results.

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