@inbook{655a1067f3d0419c92c112809eb2518b,
title = "Increasing the network capacity for multi-modal multi-hop WSNs through unsupervised data rate adjustment",
abstract = "We propose to improve the quality of data for data fusion in a wireless sensor network deployed in an urban environment by dynamically controlling the transmission rate of the sensors. When nodes are grouped in multi-hop clusters, this mechanism will increase the number of messages being received at the cluster heads. We implement a previously proposed cross-layer data adjustment algorithm and integrate it into our multi-modal dynamic clustering algorithm MDSTC. Extensive simulations in NS2 using a simpler two-hop cluster show that using the data rate algorithm allows for better efficiency within the cluster.",
author = "Matthew Jones and Doina Bein and Madan, {Bharat B.} and Shashi Phoha",
note = "Funding Information: This material is based upon work supported by, or in part by, the U. S. Army Research Laboratory and the U. S. Army Research Office under the eSensIF MURI Award No. W911NF-07-1-0376. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsor.",
year = "2011",
doi = "10.1007/978-3-642-24013-3_18",
language = "English (US)",
isbn = "9783642240126",
series = "Studies in Computational Intelligence",
pages = "183--193",
editor = "Brazier, {Frances M.T.} and Kees Nieuwenhuis and Gregor Pavlin and Martijn Warnier and Costin Badica",
booktitle = "Intelligent Distributed Computing V",
}