An Adjusted Free-Market-Inspired Approach to Mitigate Free-Riding Behavior in Peer-to-Peer Fog Computing

Abstract

Peer-to-peer (P2P) architecture is increasingly gaining attention as a potential solution for the scalability problem facing the Internet of Things (IoT). It can be adopted for the fog computing layer to sustain the massive flow of data from constrained IoT nodes to the cloud. The success of a P2P-based system is entirely dependent on the continuity of resource sharing among individual nodes. Free riding is a severe problem that contradicts this main principle of P2P systems. It is understood that peers tend to consume resources from other peers without offering any in return. This free riding behavior can decrease system scalability and content availability, resulting in a decline in performance. Significant efforts have been made to hinder this behavior and to encourage cooperation amongst peers. To this end, we propose AFMIA, an Adjusted Free-Market-Inspired Approach that considers resources as goods that have dynamic prices based on the amount of supply and demand. Peers have wealth that can be increased by providing resources and spent by consuming them. The experimental results indicate that the proposed algorithm can successfully improve fairness without compromising on success rates.