@inproceedings{576c29945d8d44e4aeccb8ea668fff6b,
title = "An energy-efficient and density -aware clustering for WSNs",
abstract = "Wireless Sensor Networks are sets of thousands or more of sensor nodes with very small size and limited energy, scattered over particular area to sense a certain physical phenomenon. Energy constraints are the most important challenge for these networks to work efficiently for long time. Most existing clustering algorithms are applied without considering the density of region. In this paper, density-aware clustering algorithm that based on region density and uses fuzzy clustering technique in cluster formation is proposed.The cluster head selection method depends on intra and inter-communication distances in addition to residual energy. It is cluster-based, centralized, single-hop routing method. The simulation results show that the algorithm can balance the energy load between nodes, reduce energy consumption and prolong the stability period and life time of network compared to traditional LEACH-C.",
keywords = "cluster-based, density-aware, inter-communication, intra-communication, subtractive clustering",
author = "Khamiss, {A. A.} and Senchun Chai and Baihai Zhang and Jingye Luan and Qiao Li",
note = "Publisher Copyright: {\textcopyright} 2014 TCCT, CAA.; Proceedings of the 33rd Chinese Control Conference, CCC 2014 ; Conference date: 28-07-2014 Through 30-07-2014",
year = "2014",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2014.6896652",
language = "English",
series = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
publisher = "IEEE Computer Society",
pages = "377--382",
editor = "Shengyuan Xu and Qianchuan Zhao",
booktitle = "Proceedings of the 33rd Chinese Control Conference, CCC 2014",
address = "United States",
}