TU Darmstadt / ULB / TUbiblio

Evaluation Study for Clustering in Wireless Sensor Networks

Stein, Michael and Lerbs, Dominic and Hassan, Mohamed and Schnee, Mathias and Schweizer, Immanuel and Weihe, Karsten and Mühlhäuser, Max (2016):
Evaluation Study for Clustering in Wireless Sensor Networks.
In: Proceedings of IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), [Conference or Workshop Item]

Abstract

Typically, wireless sensor nodes are battery- powered. The network's lifetime depends on the energy consumption of the sensor nodes. Transmitting messages causes a good portion of this energy consumption. Clustering the sensor nodes may reduce energy consumption through local communication and aggregation. Many clustering algorithms exist, but corresponding simulation results are hardly comparable. This paper conducts an extensive simulation study. We compare five popular clustering algorithms in four different scenarios under strictly uniform conditions. Our results indicate that two criteria for clustering algorithms are particularly important: considering residual energy for cluster head selection, and small communication overhead during cluster formation.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Stein, Michael and Lerbs, Dominic and Hassan, Mohamed and Schnee, Mathias and Schweizer, Immanuel and Weihe, Karsten and Mühlhäuser, Max
Title: Evaluation Study for Clustering in Wireless Sensor Networks
Language: English
Abstract:

Typically, wireless sensor nodes are battery- powered. The network's lifetime depends on the energy consumption of the sensor nodes. Transmitting messages causes a good portion of this energy consumption. Clustering the sensor nodes may reduce energy consumption through local communication and aggregation. Many clustering algorithms exist, but corresponding simulation results are hardly comparable. This paper conducts an extensive simulation study. We compare five popular clustering algorithms in four different scenarios under strictly uniform conditions. Our results indicate that two criteria for clustering algorithms are particularly important: considering residual energy for cluster head selection, and small communication overhead during cluster formation.

Divisions: DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
Zentrale Einrichtungen
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology > Subproject A1: Modelling
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms > Teilprojekt B2: Planung und Koordination
Event Title: Proceedings of IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)
Date Deposited: 07 Jun 2016 08:09
Export:
Suche nach Titel in: TUfind oder in Google

Optionen (nur für Redakteure)

View Item View Item