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Sensors (Basel). 2018 Aug 27;18(9). pii: E2819. doi: 10.3390/s18092819.

Internet of Bikes: A DTN Protocol with Data Aggregation for Urban Data Collection.

Author information

1
Telecommunications Department, University of Lyon, INSA Lyon, Inria, CITI F-69621 Villeurbanne, France. yosra.zguira@insa-lyon.fr.
2
NOCCS Laboratory Higher Institute of Computer Science and Communication Technologies, ISITCom, University of Sousse Sahloul, Sousse 4054, Tunisia. yosra.zguira@insa-lyon.fr.
3
Telecommunications Department, University of Lyon, INSA Lyon, Inria, CITI F-69621 Villeurbanne, France. Herve.Rivano@inria.fr.
4
NOCCS Laboratory, National Engineering School, ENISO, University of Sousse, Sousse 4054, Tunisia. Aref.Meddeb@infcom.rnu.tn.

Abstract

Intelligent Transport Systems (ITS) are an essential part of the global world. They play a substantial role for facing many issues such as traffic jams, high accident rates, unhealthy lifestyles, air pollution, etc. Public bike sharing system is one part of ITS and can be used to collect data from mobiles devices. In this paper, we propose an efficient, "Internet of Bikes", IoB-DTN routing protocol based on data aggregation which applies the Delay Tolerant Network (DTN) paradigm to Internet of Things (IoT) applications running data collection on urban bike sharing system based sensor network. We propose and evaluate three variants of IoB-DTN: IoB based on spatial aggregation (IoB-SA), IoB based on temporal aggregation (IoB-TA) and IoB based on spatiotemporal aggregation (IoB-STA). The simulation results show that the three variants offer the best performances regarding several metrics, comparing to IoB-DTN without aggregation and the low-power long-range technology, LoRa type. In an urban application, the choice of the type of which variant of IoB should be used depends on the sensed values.

KEYWORDS:

LoRa/LoRaWAN; data aggregation; data collection; delay tolerant networks; internet of bikes; internet of things; low-power long-range technology; smart cities; wireless sensor networks

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