Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs
Wireless sensor networks (WSNs) consist of a large number of sensor nodes equipped with a diverse number of small and low-cost devices with limited resources, such as a short communication range, a low bandwidth, a small memory, and a restricted energy. In particular, among these constraint factors,...
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2014-03-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2014/670962 |
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doaj-5dbac67d26624fd784d45d979c76ff372020-11-25T03:10:04ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-03-011010.1155/2014/670962670962Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNsJoon-Ik Kong0Jin-Woo Kim1Doo-Seop Eom2 Department of Electric Engineering, Korea University, Seoul 136-075, Republic of Korea Research Institute of Information Science and Engineering, Mokpo National University, Mokpo 534-729, Republic of Korea Department of Electric Engineering, Korea University, Seoul 136-075, Republic of KoreaWireless sensor networks (WSNs) consist of a large number of sensor nodes equipped with a diverse number of small and low-cost devices with limited resources, such as a short communication range, a low bandwidth, a small memory, and a restricted energy. In particular, among these constraint factors, a sensor node's energy consumption is a very important factor in extending a network's lifetime. Many researchers are focused on the energy efficiency of wireless sensor networks. Many clustering algorithms have been proposed to improve energy efficiency. However, most protocols in previous literature have the problem of not considering the characteristics of real applications, for example, forest fire detection, intruder detection, target tracking, and the like. In this paper, we propose an energy-efficient clustering algorithm that can respond rapidly to unexpected events with increased energy efficiency, because each sensor node detects events individually and creates clusters using a regional competition scheme. Simulation results show improved performance when our algorithm is used.https://doi.org/10.1155/2014/670962 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Joon-Ik Kong Jin-Woo Kim Doo-Seop Eom |
spellingShingle |
Joon-Ik Kong Jin-Woo Kim Doo-Seop Eom Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs International Journal of Distributed Sensor Networks |
author_facet |
Joon-Ik Kong Jin-Woo Kim Doo-Seop Eom |
author_sort |
Joon-Ik Kong |
title |
Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs |
title_short |
Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs |
title_full |
Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs |
title_fullStr |
Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs |
title_full_unstemmed |
Energy-Aware Distributed Clustering Algorithm for Improving Network Performance in WSNs |
title_sort |
energy-aware distributed clustering algorithm for improving network performance in wsns |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2014-03-01 |
description |
Wireless sensor networks (WSNs) consist of a large number of sensor nodes equipped with a diverse number of small and low-cost devices with limited resources, such as a short communication range, a low bandwidth, a small memory, and a restricted energy. In particular, among these constraint factors, a sensor node's energy consumption is a very important factor in extending a network's lifetime. Many researchers are focused on the energy efficiency of wireless sensor networks. Many clustering algorithms have been proposed to improve energy efficiency. However, most protocols in previous literature have the problem of not considering the characteristics of real applications, for example, forest fire detection, intruder detection, target tracking, and the like. In this paper, we propose an energy-efficient clustering algorithm that can respond rapidly to unexpected events with increased energy efficiency, because each sensor node detects events individually and creates clusters using a regional competition scheme. Simulation results show improved performance when our algorithm is used. |
url |
https://doi.org/10.1155/2014/670962 |
work_keys_str_mv |
AT joonikkong energyawaredistributedclusteringalgorithmforimprovingnetworkperformanceinwsns AT jinwookim energyawaredistributedclusteringalgorithmforimprovingnetworkperformanceinwsns AT dooseopeom energyawaredistributedclusteringalgorithmforimprovingnetworkperformanceinwsns |
_version_ |
1724660812056887296 |