A framework for reliable and ubiquitous inference in wireless sensor network

Development of Internet of things (IoT) applications brings a new movement to the functionality of wireless sensor networks (WSNs) from only environment sensing and data gathering to collaborative inferring and ubiquitous intelligence. In intelligent WSNs, nodes collaborate to exchange the information needed to achieve the required inference or smartness. Efficiency or correctness of many smart applications rely on efficient, timely, reliable, and ubiquitous inference of information which may continually change in interaction with other nodes. In this paper, we introduce a framework which provides a generic solution for such common ubiquitous inferences. This framework brings the reliability and ubiquity for inferences using the redundancy characteristic of the gossiping protocols. With this framework the implementation of such inferences and the control of their speed and cost is abstracted by providing the developers with a proposed middleware and some dissemination control services. We develop a prototype implementation of the proposed framework and an inference example on TinyOS to evaluate the effectiveness of the framework and the efficiency of the related inferences. To this aim, we utilize TOSSIM simulator in various densities and different number of nodes. Results of the evaluations demonstrate that in all nodes, the inferring time after a change is about a few seconds (less than a minute) and the cost of maintenance in steady state is about a few sends (less than 10) per hour.