An Ontology-Driven Framework for Resource-Efficient Collaborative Sensing

Abstract

The massive adoption of smartphones that incorporate wireless connectivity and a growing set of embedded sensors is leveraging the emergence of personal and community-scale sensing applications. In these applications, the smartphones act as a cloud of sensors that move around with their human users and hence, are capable of gathering a rich variety of data from their users and from their environments. However, in order to realize their full potential, the designers of these applications face a set of technical challenges related with the limited resources available to mobile devices, their heterogeneity, and the dynamics of the scenarios where they are deployed. In this paper we introduce an ontology-driven framework aimed at efficiently supporting collaborative opportunistic sensing tasks. The proposed framework is composed of a set of local and distributed algorithms that support the establishment and coordination of sensing tasks by performing in-network processing to locate the devices that are most fit to perform the task and by establishing routes that can be used to exchange information among relevant devices. We present theorems that prove that the proposed algorithms are correct.