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Sensors 2016, 16(11), 1852; doi:10.3390/s16111852

An Arrival and Departure Time Predictor for Scheduling Communication in Opportunistic IoT

1
Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, UK
2
Digital Catapult Centre, London NW1 2RA, UK
3
Dunav Net, Novi Sad 21000, Serbia
*
Author to whom correspondence should be addressed.
Academic Editors: Andrea Zanella and Toktam Mahmoodi
Received: 26 July 2016 / Revised: 19 October 2016 / Accepted: 24 October 2016 / Published: 4 November 2016
(This article belongs to the Special Issue Smart City: Vision and Reality)
View Full-Text   |   Download PDF [8874 KB, uploaded 4 November 2016]   |  

Abstract

In this article, an Arrival and Departure Time Predictor (ADTP) for scheduling communication in opportunistic Internet of Things (IoT) is presented. The proposed algorithm learns about temporal patterns of encounters between IoT devices and predicts future arrival and departure times, therefore future contact durations. By relying on such predictions, a neighbour discovery scheduler is proposed, capable of jointly optimizing discovery latency and power consumption in order to maximize communication time when contacts are expected with high probability and, at the same time, saving power when contacts are expected with low probability. A comprehensive performance evaluation with different sets of synthetic and real world traces shows that ADTP performs favourably with respect to previous state of the art. This prediction framework opens opportunities for transmission planners and schedulers optimizing not only neighbour discovery, but the entire communication process. View Full-Text
Keywords: internet of things; neighbour discovery; predictor; opportunistic; scheduling internet of things; neighbour discovery; predictor; opportunistic; scheduling
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MDPI and ACS Style

Pozza, R.; Georgoulas, S.; Moessner, K.; Nati, M.; Gluhak, A.; Krco, S. An Arrival and Departure Time Predictor for Scheduling Communication in Opportunistic IoT. Sensors 2016, 16, 1852.

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