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Conference Papers Year : 2018

For An Efficient Internet of Bikes : A DTN Routing Protocol Based On Data Aggregation Approach

Abstract

Nowadays, cities are facing an increasing number of bikes used by citizens therefore the need of monitoring and managing their traffic becomes crucial. With the development of Intelligent Transport Systems (ITS) in smart city, public bike sharing system has been considered as an urban transportation system that can collect data from mobile devices. In such network, the biggest challenge for sensor nodes is to forward data to sinks in an energy efficient way because of the following limitations: limited energy resources, limited storage capacity and limited bandwidth. Data aggregation is a key mechanism to save energy consumption and network capacity. It can be defined as an approach to combine data of various sensors into a single packet, thus reducing sensor communication costs and achieving a longer network lifetime. The main contribution of this paper is to introduce an efficient, "Internet of Bikes", IoB-DTN routing protocol based on data aggregation being applied to mobile network IoT devices running a data collection application on urban bike sharing system based sensor network. We propose three variants of IoB-DTN: IoB based on spatial aggregation (IoB-SA), IoB based on temporal aggregation (IoB-TA) and IoB based on spatio-temporal aggregation (IoB-STA). We compare the three variants with the multi-hop IoB-DTN protocol without aggregation and the low-power long-range technology, LoRa type. Comparison results verify that the three variants of IoB-DTN based on data aggregation improve the delivery rate, energy consumption and throughput.
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Dates and versions

hal-01887567 , version 1 (04-10-2018)

Identifiers

Cite

Yosra Zguira, Herve Rivano, Aref Meddeb. For An Efficient Internet of Bikes : A DTN Routing Protocol Based On Data Aggregation Approach. PEWASUN 2018 - 15th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks, Oct 2018, Montreal, Canada. ⟨10.1145/3243046.3243048⟩. ⟨hal-01887567⟩
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