Participant recruitment and data collection framework for opportunistic sensing

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.