Fair Pricing In Heterogeneous Internet of Things Wireless Access Networks Using Crowdsourcing

TL;DR

This paper introduces a crowdsourcing-based pricing model for IoT wireless networks that ensures fair pricing above marginal costs, prevents collusion, and adapts to client preferences within an oligopoly market.

Contribution

It presents a novel three-tier pricing framework incorporating regulatory constraints, client preferences, and provider strategies for fair IoT wireless service pricing.

Findings

Model converges only when one provider announces the fair price.

Approach prevents collusion among network providers.

Pricing adapts dynamically to client preferences and costs.

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 has 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 paper, we propose a novel crowdsourcing-based approach for fair wireless service pricing in Internet of Things (IoT). In our considered oligopoly, the regulatory sets a dynamic maximum allowed price of service to prevent anti-trust behaviour 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 converges only if one network announces the fair price