Quality of Contributed Service and Market Equilibrium for Participatory Sensing
User-contributed or crowd-sourced information is becoming increasingly common. In this paper, we consider the specific case of participatory sensing whereby people contribute information captured by sensors, typically those on a smartphone, and share the information with others. We propose a new metric called quality of contributed service (QCS) which characterizes the information quality and timeliness of a specific real-time sensed quantity achieved in a participatory manner. Participatory sensing has the problem that contributions are sporadic and infrequent. To overcome this, we formulate a market-based framework for participatory sensing with plausible models of the market participants comprising data contributors, service consumers and a service provider. We analyze the market equilibrium and obtain a closed form expression for the resulting QCS at market equilibrium. Next, we examine the effects of realistic behaviors of the market participants and the nature of the market equilibrium that emerges through extensive simulations. Our results show that, starting from purely random behavior, the market and its participants can converge to the market equilibrium with good QCS within a short period of time.
C. Tham and T. T. Luo, "Quality of Contributed Service and Market Equilibrium for Participatory Sensing," IEEE Transactions on Mobile Computing, vol. 14, no. 4, pp. 829 - 842, Institute of Electrical and Electronics Engineers (IEEE), Apr 2015.
The definitive version is available at https://doi.org/10.1109/TMC.2014.2330302
Keywords and Phrases
incentive; Mobile computing; network economics; participatory sensing
International Standard Serial Number (ISSN)
Article - Journal
© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Apr 2015
Most of this work was done when Tie Luo was at the Department of Electrical and Computer Engineering, National University of Singapore, under the EDASACEP project which was part of the DVCaaS TSRP research programme funded by SERC, A*STAR Singapore.