Utility-driven data acquisition in participatory sensing

  • Authors:
  • Mehdi Riahi;Thanasis G. Papaioannou;Immanuel Trummer;Karl Aberer

  • Affiliations:
  • École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

  • Venue:
  • Proceedings of the 16th International Conference on Extending Database Technology
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Participatory sensing (PS) is becoming a popular data acquisition means for interesting emerging applications. However, as data queries from these applications increase, the sustainability of this platform for multiple concurrent applications is at stake. In this paper, we consider the problem of efficient data acquisition in PS when queries of different types come from different applications. We effectively deal with the issues related to resource constraints, user privacy, data reliability, and uncontrolled mobility. We formulate the problem as multi-query optimization and propose efficient heuristics for its effective solution for the various query types and mixes that enable sustainable sensing. Based on simulations with real and artificial data traces, we found that our heuristic algorithms outperform baseline approaches in a multitude of settings considered.