Fog computing is an emerging service-oriented market in conjunction with Cloud computing to fulfill the resource demand of mobile users as well as IoT users for real-time applications. Auctioning in Fog computing is highly challenging due to mobility, dynamic pricing, real-time demand in comparison to Cloud based auctioning models. Further, due to users’ mobility and limited Fog resources, existing reverse auction techniques developed for Cloud computing model cannot directly be applied for the resource procurement in Fog-Integrated Cloud Architecture (FICA). Therefore, a reverse auction-based model which includes customer, auctioneer, Fog provider, Cloud provider, and Fog & Cloud provider together as auction participants, is proposed in this work. The proposed model, for resource provisioning using a multi-attribute combinatorial reverse auction, is named as Fog-Integrated Cloud Auctioning Model (FICAM). FICAM pricing scheme includes three types of resources depending on their requirement i.e., local Fog, remote Fog, and Cloud. A truthful, robust, and fair algorithm for resource allocation is proposed considering response time, data source mobility requirements, and Fog resource limitations. To encourage providers to bid truthfully, the Vickrey model is extended. FICAM also introduces a new algorithm for resource procurement in which instead of giving all resources of the bundle, only the required resources at a time are given to the customer with the bundle discount. The discount is based on a certain threshold in the ratio of the availed amount of resources to the offered amount of resources. Rigorous experimentation exhibits that the proposed model offers a low resource procurement cost in polynomial time as compared to other state of the art algorithms.

雾计算与云计算结合在一起是一个新兴的面向服务的市场，可以满足移动用户以及物联网用户对实时应用程序的资源需求。与基于云的拍卖模型相比，由于移动性，动态定价和实时需求，雾计算中的拍卖具有很高的挑战性。此外，由于用户的移动性和有限的Fog资源，为云计算模型开发的现有反向拍卖技术无法直接应用于Fog-Integrated Cloud Architecture（FICA）中的资源采购。因此，在这项工作中，提出了一个基于反向拍卖的模型，该模型包括客户，拍卖人，雾提供者，云提供者以及雾和云提供者一起作为拍卖参与者。建议的模型，使用多属性组合反向拍卖进行资源配置的服务被称为雾集成云拍卖模型（FICAM）。FICAM定价方案根据其需求包括三种类型的资源，即本地雾，远程雾和云。考虑到响应时间，数据源移动性要求和Fog资源限制，提出了一种真实，鲁棒，公平的资源分配算法。为了鼓励供应商如实竞标，对Vickrey模型进行了扩展。FICAM还引入了一种用于资源采购的新算法，该算法不是给捆绑包中的所有资源，而是一次仅向捆绑包折扣中的客户提供所需的资源。折扣基于资源的可用量与提供的资源量之比中的某个阈值。