You better be honest: Discouraging free-riding and false-reporting in mobile crowdsourcing

Xiang Zhang, Guoliang Xue, Ruozhou Yu, Dejun Yang, Jian Tang

Research output: Contribution to journalConference Articlepeer-review

10 Scopus citations


Crowdsourcing is an emerging paradigm where users can pay for the services they need or receive rewards for providing services. One example in wireless networking is mobile crowdsourcing, which leverages a cloud computing platform for recruiting mobile users to collect data (such as photos, videos, mobile user activities, etc) for applications in various domains, such as environmental monitoring, social networking, healthcare, transportation, etc. However, a critical problem arises as how to ensure that users pay or receive what they deserve. Free-riding and false-reporting may make the system vulnerable to dishonest users. In this paper, we aim to design schemes to tackle these problems, so that each individual in the system is better off being honest. We first design a mechanism EFF which eliminates dishonest behavior with the help from a trusted third party for arbitration. We then design another mechanism DFF which, without the help from any third party, discourages free-riding and false-reporting. We prove that EFF eliminates the existence of free-riding and false-reporting, while guaranteeing truthfulness, individual rationality, budget-balance, and computational efficiency. We also prove that DFF is semi-truthful, which discourages dishonest behavior such as free-riding and false-reporting when the rest of the individuals are honest, while guaranteeing budget-balance and computational efficiency. Performance evaluation shows that within our mechanisms, no dishonest behavior could bring extra benefit for each individual.

Original languageEnglish (US)
Article number7037593
Pages (from-to)4971-4976
Number of pages6
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
StatePublished - 2014
Event2014 IEEE Global Communications Conference, GLOBECOM 2014 - Austin, United States
Duration: Dec 8 2014Dec 12 2014

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


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