A Game-Theoretic Analysis of User Behaviors in Crowdsourced Wireless Community Networks

TL;DR

This paper models user behavior in crowdsourced wireless networks using a two-stage game, analyzing equilibrium strategies and how they influence network performance and operator incentives.

Contribution

It introduces a novel game-theoretic framework for joint membership and access decisions in wireless community networks, providing equilibrium analysis and optimization insights.

Findings

Users with popular home locations prefer Bill membership

Mobility and access evaluations influence membership choices

Operators can optimize pricing based on equilibrium analysis

Abstract

A crowdsourced wireless community network can effectively alleviate the limited coverage issue of Wi-Fi access points (APs), by encouraging individuals (users) to share their private residential Wi-Fi APs with each other. This paper presents the first study on the users' joint membership selection and network access problem in such a network. Specifically, we formulate the problem as a two-stage dynamic game: Stage I corresponds to a membership selection game, in which each user chooses his membership type; Stage II corresponds to a set of network access games, in each of which each user decides his WiFi connection time on the AP at his current location. We analyze the Subgame Perfect Equilibrium (SPE) systematically, and study whether and how best response dynamics can reach the equilibrium. Through numerical studies, we further explore how the equilibrium changes with the users' mobility patterns and network access evaluations. We show that a user with a more popular home location, a smaller travel time, or a smaller network access evaluation is more likely to choose a specific type of membership called Bill. We further demonstrate how the network operator can optimize its pricing and incentive mechanism based on the game equilibrium analysis in this work.