Increasing the network capacity for multi-modal multi-hop WSNs through unsupervised data rate adjustment

Matthew Jones, Doina Bein, Bharat B. Madan, Shashi Phoha

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationIntelligent Distributed Computing V
Subtitle of host publicationProceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, Delft, The Netherlands - October 2011
EditorsFrances M.T. Brazier, Kees Nieuwenhuis, Gregor Pavlin, Martijn Warnier, Costin Badica
Pages183-193
Number of pages11
DOIs
StatePublished - 2011

Publication series

NameStudies in Computational Intelligence
Volume382
ISSN (Print)1860-949X

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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