An Incentive Framework for Collaborative Sensing in Fog Networks

As the big data era arrives, massive data traffic and applications generated by various terminal devices need to be processed in real time. To relieve the pressure of cloud computing on link congestion, delay, and energy consumption caused by the long distance between terminals and cloud server, the promising fog computing has been proposed. The fog network consisting of several fog clusters is considered, in which a fog controller (Gamma mathrmC) collects all the resource information of all its fog nodes (FNs). In order to better serve the terminal nodes, different FCs are willing to exchange the information of their FNs and share their services to some extent. Therefore, in this paper, we propose a novel incentive framework for collaborative sensing to motivate the fog cluster to provide service for other fog clusters. The SRs use the computation reward prices to motivate the SP to provide more computational capability to complete the tasks. The utility functions of the SRs and the SP are proposed, considering the payment for task computation, the task delay and the computation cost. The existences of the global optimums of both the utilities for the SRs the SP are proved. Numerous simulations verify our theoretical analyses and indicate the importance of our proposed incentive framework for collaborative sensing between fog clusters subscribed to different mobile providers in the fog network.