Imperial College London
Alternate

DrJavierBarria

Faculty of Engineering, Department of Electrical and Electronic Engineering

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Contact

 

+44 (0)20 7594 6275j.barria Website

 
 
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Location

 

1012Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Milojevic:2017:10.1109/MTITS.2017.8005674,
author = {Milojevic, M and Barria, J},
doi = {10.1109/MTITS.2017.8005674},
pages = {244--249},
publisher = {IEEE},
title = {Early warnings dissemination for urban micro-scale monitoring using vehicular sensor network},
url = {http://dx.doi.org/10.1109/MTITS.2017.8005674},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - This paper presents the beaconless multi-hop Decentralised Dissemination of Warnings (DDW) mechanism for micro-scale monitoring applications in urban environments. It is designed for a Vehicular Sensor Network (VSN) based on mobile nodes with limited resources. Mobile nodes sense and generate high pollution levels early warnings in near real-time. The warning messages are disseminated toward Static Monitoring Units used by the local authorities to monitor onsets of harmful pollution level episodes. The DDW is a distance-based mechanism where a receiving node calculates the waiting time before rebroadcasting the message based on the distance from the sending node and the distance to the Static Monitoring Units. The DDW mechanism performance is evaluated in an urban environment with different number of mobile nodes in the network. Results show that the proposed mechanism collects more non-duplicated warnings at the Static Monitoring Units than other evaluated dissemination protocols. It is also shown the DDW mechanism reduces the amount of duplicated warning messages sent in the network, which is especially important when mobile nodes are resource constrained.
AU  - Milojevic,M
AU  - Barria,J
DO  - 10.1109/MTITS.2017.8005674
EP  - 249
PB  - IEEE
PY  - 2017///
SP  - 244
TI  - Early warnings dissemination for urban micro-scale monitoring using vehicular sensor network
UR  - http://dx.doi.org/10.1109/MTITS.2017.8005674
UR  - http://hdl.handle.net/10044/1/48599
ER  -
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