Next Article in Journal
Multi-instrumental Investigation of Affecting of Early Somatic Embryos of Spruce by Cadmium(II) and Lead(II) Ions
Previous Article in Journal
Horseradish Peroxidase (HRP) Immobilized Poly(aniline-co-m-aminophenol) Film Electrodes–fabrication and Evaluation as Hydrogen Peroxide Sensor
Article Menu

Export Article

Open AccessArticle
Sensors 2007, 7(5), 730-742;

Optimized Self Organized Sensor Networks

School of Computer Science and Engineering, Chung-Ang University 221, Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea
Center of Excellence for Quantifiable Quality of Service (Q2S), Norwegian University of Science and Technology, Norway
Author to whom correspondence should be addressed.
Received: 26 April 2007 / Accepted: 30 May 2007 / Published: 31 May 2007
Full-Text   |   PDF [308 KB, uploaded 21 June 2014]


Wireless sensor networks are composed of a huge number of sensor nodes, which have limited resources - energy, memory and computation power. Energies are directly related to the lifetime of sensor network. If sensor nodes can be grouped to clusters, cluster member sensor nodes only need to communicate with cluster center (head) and this leads to energy conservation of the member sensors. So, how to compose clusters with minimal number of cluster heads, while including each node in a cluster is an important research issue. We propose a new advanced optimization algorithm for sensor network clustering. Using the proposed optimization algorithm, redundant cluster heads are eliminated, and unnecessarily overlapped clusters are merged. Optimization algorithm can be used as a clustering algorithm by itself and also manage the dynamic changes like node addition or die-out, while the network is even on the working state. We tested the proposed method as a clustering algorithm and compared it with two other recent sensor network clustering algorithms, Algorithm for Cluster Establishment (ACE) and Self Organizing Sensor network algorithm (SOS). The experiments results not only illustrate that the proposed algorithm could result in clusters with smaller number of cluster heads than others with any density of sensor networks, but also that the performance is more stable, which is also verified through repeated experiments. View Full-Text
Keywords: Optimization of clustering algorithm; Self Organizing Sensor algorithm; Intelligent Clustering; Wireless Sensor Network Optimization of clustering algorithm; Self Organizing Sensor algorithm; Intelligent Clustering; Wireless Sensor Network
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Park, S.; Shin, K.; Abraham, A.; Han, S. Optimized Self Organized Sensor Networks. Sensors 2007, 7, 730-742.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top