Profit-Maximizing Incentive for
Participatory Sensing
IEEE INFOCOM 2014
Tie Luo, Hwee-Pink Tan (Institute for Infocomm Research, Singapore)
and Lirong Xia (Rensselaer Polytechnic Institute, USA)
2015.2.24
Yunhyoung Kim
Table of Contents
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•
•
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Introduction
Model
Analysis
Case Study
Summary and Conclusion
Introduction
Participatory Sensing:
“A citizen-powered approach to illuminating the patterns that shape our world”
Participatory Sensing Example : PEIR, ParkNet, Ear-Phone
How to encourage people to participate?
Introduction
All-Pay Auction
Contribute to sensing
Give an award to the winner
Principal
Agents
Differences from Vickery auction : all the agents should pay their bids
Main contributions of this paper
Principal’s Profit Maximization : max     contribution    cost of prize 
Extended assumption on agents : Risk-neutral & Risk-averse agents
Stochastic Population : the number of agents is endogenized
Incomplete information with information asymmetry : do not know about other’s type
Model
Notation

Principal’s profit function :
Agent’s payoff function :
Model

Principal’s profit function :
Agent’s payoff function :
Problem Statement
Find M(⋅) which
1) maximizes expected profit of principal at equilibrium,
2) satisfies strict individual rationality (for weakly risk-averse & risk-neutral agents)
Analysis
1. Find equilibrium contribution strategy
2. Find optimal prize function
, given
Agents
Expected Payoff :
Prob. of winning (with type s) :
Lemma 2. The equilibrium contribution strategy
is determined by
Principal
Analysis
2. Find optimal prize function
, given

Explicit expression of
Assumption : Agents are weakly risk-averse

is necessary.
Analysis
Theorem 1. Optimal prize fuction is given by
Theorem 2. Given optimal prize function, the equilibrium strategy satisfies strict individual
rationality.
Analysis
Applying to specific situations : 1. Risk-neutral Agents
Corollary 1. Equilibrium contribution strategy is determined by
Corollary 2. Optimal prize function is given by
Applying to specific situations : 2. Deterministic Population
Equilibrium contribution strategy and optimal prize function can be obtained by
substituting
RN-DP :
Applying to specific situations : 3. RN-DP with Constant Prize
Corollary 3. Equilibrium contribution strategy and optimal prize function :
Case Study
Using specific functions :
Risk averse, stochastic population
Risk neutral, deterministic population
Summary and Conclusion
All-pay auction as an encouraging strategy for participatory sensing
Profit maximizing prize function dependent on maximum contribution and
the number of participants
Contribution-dependent prize outperforms constant prize
: Leveraging risk-averse agents’fear of losing auctions