Collaborative Incentive Mechanism for Mobile Crowdsensing

Youqi Li*, Fan Li, Song Yang, Chuan Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this chapter, we propose PTASIM, an incentive mechanism that explores cooperation with POI-tagging App for Mobile Edge Crowdsensing (MEC). PTASIM requests the App to tag some edges to be POI (Points-of-Interest), which further guides App users to perform tasks at that location. We further model the interactions of users, a platform, and an App by a three-stage decision process. The App first determines the POI-tagging price to maximize its payoff. Platform and users subsequently decide how to determine tasks reward and select edges to be tagged, and how to select the best task to perform, respectively. We analyze the optimal solution in those stages. Specifically, we prove greedy algorithm could provide the optimal solution for the platform’s payoff maximization in polynomial time. The numerical results show that: (1) the cooperation with App brings long-term and sufficient participation; the optimal strategies reduce the platform’s tasks cost as well as improve App’s revenues.

Original languageEnglish
Title of host publicationSpringerBriefs in Computer Science
PublisherSpringer
Pages71-93
Number of pages23
DOIs
Publication statusPublished - 2024

Publication series

NameSpringerBriefs in Computer Science
VolumePart F2071
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776

Keywords

  • POI-tagging App
  • Participation rate guarantee
  • Stackelberg game
  • Third-party collaboration
  • Three-stage decision process

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