Participant recruitment and data collection framework for opportunistic sensing: a comparative analysis

  • Authors:
  • Guliz S. Tuncay;Giacomo Benincasa;Ahmed Helmy

  • Affiliations:
  • University of Florida, Gainesville, FL, USA;University of Florida, Gainesville, FL, USA;University of Florida, Gainesville, FL, USA

  • Venue:
  • Proceedings of the 19th annual international conference on Mobile computing & networking
  • Year:
  • 2013

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Abstract

Opportunistic sensing is a novel approach that exploits the sensing capabilities offered by smartphones and users' mobility to sense large scale areas without requiring the deployment of sensors in-situ. In this work, we propose a novel framework for fully distributed, opportunistic sensing which coherently integrates two main components that operate in DTN mode: i. participant recruitment and ii. data collection. We evaluate our approach by considering alternative implementations of the framework, and by measuring their performance via extensive trace-based simulations. Our results show how the performances of the considered protocols vary, depending on the particular scenario, and suggest guidelines for future development of distributed opportunistic sensing systems.