F-ETX: a predictive link state estimator for mobile networks

Sébastien Bindel; Serge Chaumette; Benoît Hilt

Research Article

F-ETX: a predictive link state estimator for mobile networks

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@ARTICLE{10.4108/eai.20-6-2016.151517,
    author={S\^{e}bastien Bindel and Serge Chaumette and Beno\"{\i}t Hilt},
    title={F-ETX: a predictive link state estimator for mobile networks},
    journal={EAI Endorsed Transactions on Mobile Communications and Applications},
    volume={2},
    number={7},
    publisher={EAI},
    journal_a={MCA},
    year={2016},
    month={6},
    keywords={MANET, link quality, forecasting, routing},
    doi={10.4108/eai.20-6-2016.151517}
}

Sébastien Bindel
Serge Chaumette
Benoît Hilt
Year: 2016
F-ETX: a predictive link state estimator for mobile networks
MCA
EAI
DOI: 10.4108/eai.20-6-2016.151517

Sébastien Bindel¹, Serge Chaumette¹^,*, Benoît Hilt²

1: LaBRI, University of Bordeaux, France
2: MIPS, University of Haute Alsace, France

*Contact email: serge.chaumette@labri.fr

Abstract

Due to their inherent features, Mobile Ad Hoc Networks have proven their efficiency to exchange data between mobile nodes. The main issue in this type of a network is the delivery of data to a destination. Unfortunately, the mobility of nodes and the disturbances of the propagation channel lead to the increase of the loss rate, which undermines routing performances. To address this issue, routing protocols use link quality estimators as a metric. However, current estimators have been designed for static wireless sensor networks and are not suitable in case of mobility. In order to overcome this issue, a novel metric called Fast ETX is suggested, which gives a reliable and accurate link quality assessment. It is setup by four estimators which assess and predict the link state. In addition, we design a framework to integrate this multi-estimator metric into a routing protocol.

Keywords: MANET, link quality, forecasting, routing

Received: 2015-10-30
Accepted: 2016-01-02
Published: 2016-06-20
Publisher: EAI

: http://dx.doi.org/10.4108/eai.20-6-2016.151517

Copyright © 2016 Sébastien Bindel et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.