A Multi-Leader Multi-Follower Game-Based Analysis for Incentive Mechanisms in Socially-Aware Mobile Crowdsensing

Jiangtian Nie, Jun Luo, Zehui Xiong, Dusit Niyato, Ping Wang, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


The mobile crowdsensing paradigm facilitates a broad range of emerging sensing applications by leveraging ubiquitous mobile users to cooperatively perform certain sensing tasks with their smart devices. As this paradigm involves data collection from users, the issue of designing rewards to incentivize users is fundamentally important to ensure participation in crowdsensing. In this paper, we revisit this issue in the context of socially-aware crowdsensing which integrates crowdsensing into social networks. For example, in healthcare-based crowdsensing services, the fun of tracking daily nutrition information for a certain user can be promoted by comparing her nutritional information with that contributed and shared by her socially-connected friends. To be more general and practical, we study the incentive mechanisms in presence of multiple crowdsensing service providers and multiple users. Understanding the behaviors of users and service providers in socially-aware crowdsensing is of paramount importance for incentive mechanisms. With this focus, we propose a multi-leader and multi-follower Stackelberg game approach to model the strategic interactions among service providers and users, where the social influence of users and the strategic interconnections of service providers are jointly and formally integrated into the game modeling. Through backward induction methods, we theoretically prove the existence and uniqueness of the Stackelberg equilibrium. We conduct extensive simulations to investigate game equilibrium properties, and the real-world dataset is applied to evaluate and demonstrate the performance effectiveness of the proposed game model.

Original languageEnglish (US)
Article number9247464
Pages (from-to)1457-1471
Number of pages15
JournalIEEE Transactions on Wireless Communications
Issue number3
StatePublished - Mar 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


  • Socially-aware crowdsensing
  • incentive scheme
  • multi-leader multi-follower game
  • reward design


Dive into the research topics of 'A Multi-Leader Multi-Follower Game-Based Analysis for Incentive Mechanisms in Socially-Aware Mobile Crowdsensing'. Together they form a unique fingerprint.

Cite this