Fair Pricing in Heterogeneous Internet-of-Things Wireless Access Networks Using Crowdsourcing

Abstract

Price and the quality of service are two key factors taken into account by wireless network users when they choose their network provider. The recent advances in wireless technology and massive infrastructure deployments have led to better coverage, and currently at each given wirelessly covered area there are a few network providers and each have different pricing strategies. These providers can potentially set unfair expensive prices for their services. In this article, we propose a novel crowdsourcing-based approach for fair wireless service pricing in the Internet of Things (IoT). In our considered oligopoly, the regulatory sets a dynamic maximum allowed price of service to prevent anti-trust behavior and unfair service pricing. We propose a three-tire pricing model, where the regulator, wireless network providers, and clients are the players of our game. Our method takes client preferences into account in pricing and discovers the fair service pricing just above the marginal costs of each network provider. Our results show that our model is not prone to collusion and will converge only if one network announces the fair price.