Technical Report for "User-Centric Participatory Sensing: A Game Theoretic Analysis"

TL;DR

This paper models user-centric participatory sensing as a strategic game, analyzing the existence and efficiency of Nash equilibria to inform optimal user deployment.

Contribution

It introduces a game-theoretic framework for task scheduling in participatory sensing, proving the potential game nature and analyzing equilibrium efficiency and fairness.

Findings

Nash equilibrium exists in the proposed game.

Efficiency at equilibrium varies with the number of users.

More users do not always improve system performance.

Abstract

Participatory sensing (PS) is a novel and promising sensing network paradigm for achieving a flexible and scalable sensing coverage with a low deploying cost, by encouraging mobile users to participate and contribute their smartphones as sensors. In this work, we consider a general PS system model with location-dependent and time-sensitive tasks, which generalizes the existing models in the literature. We focus on the task scheduling in the user-centric PS system, where each participating user will make his individual task scheduling decision (including both the task selection and the task execution order) distributively. Specifically, we formulate the interaction of users as a strategic game called Task Scheduling Game (TSG) and perform a comprehensive game-theoretic analysis. First, we prove that the proposed TSG game is a potential game, which guarantees the existence of Nash equilibrium (NE). Then, we analyze the efficiency loss and the fairness index at the NE. Our analysis shows the efficiency at NE may increase or decrease with the number of users, depending on the level of competition. This implies that it is not always better to employ more users in the user-centric PS system, which is important for the system designer to determine the optimal number of users to be employed in a practical system.