SEW-ing a Simple Endorsement Web to incentivize trustworthy participatory sensing

• Main Authors: T. Luo, S. Kanhere, TAN, Hwee-Pink
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Nepotism; altruism; beneficiary effect; crowdsourcing; human-centric computing; social networks; web of participants; witness effect; Digital Communications and Networking
• Online Access: https://ink.library.smu.edu.sg/sis_research/2939; https://ink.library.smu.edu.sg/context/sis_research/article/3939/viewcontent/secon2014.pdf
• Institution: Singapore Management University

Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social “web of participants” with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers are interleaved to provision and enhance incentives and trustworthiness. We elaborate the social implications of SEW, and analyze the economic implications under a Stackelberg game framework. We derive the optimal design parameter that maximizes the utility of the sensing campaign organizer, while ensuring participants to strictly have incentive to participate. We also design algorithms for participants to optimally “sew” SEW, namely to manipulate the endorsement links of SEW such that their economic benefits are maximized and social constrains are satisfied. Finally, we provide two numerical examples for an intuitive understanding.