An Arrival and Departure Time Predictor for Scheduling Communication in Opportunistic IoT.
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.
Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, UK. r.pozza@surrey.ac.uk.
Riccardo
R
Pozza
Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, UK. s.georgoulas@surrey.ac.uk.
Stylianos
S
Georgoulas
Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, UK. k.moessner@surrey.ac.uk.
Klaus
K
Moessner
Digital Catapult Centre, London NW1 2RA, UK. michele.nati@digicatapult.org.uk.
Michele
M
Nati
Digital Catapult Centre, London NW1 2RA, UK. alex.gluhak@digicatapult.org.uk.
Alexander
A
Gluhak
Dunav Net, Novi Sad 21000, Serbia. srdjan.krco@dunavnet.eu.
Srdjan
S
Krco
internet of things; neighbour discovery; opportunistic; predictor; scheduling