Path: Top -> Journal -> Telkomnika -> 2016 -> Vol 14, No 3: September
Distributed Clustering Based on Node Density and Distance in Wireless Sensor Networks
Distributed Clustering Based on Node Density and Distance in Wireless Sensor Networks
Journal from gdlhub / 2016-11-08 03:31:46Oleh : Sasikumar P, Shankar T, Sibaram Khara, Telkomnika
Dibuat : 2016-09-01, dengan 1 file
Keyword : Wireless Sensor Network, Clustering, Distributed Computing, Node Density, Distance
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/2712
Wireless Sensor Networks (WSNs) are special type of network with sensing and monitoring the physical parameters with the property of autonomous in nature. To implement this autonomy and network management the common method used is hierarchical clustering. Hierarchical clustering helps for ease access to data collection and forwarding the same to the base station. The proposed Distributed Self-organizing Load Balancing Clustering Algorithm (DSLBCA) for WSNs designed considering the parameters of neighbor distance, residual energy, and node density. The validity of the DSLBCA has been shown by comparing the network lifetime and energy dissipation with Low Energy Adaptive Clustering Hierarchy (LEACH), and Hybrid Energy Efficient Distributed Clustering (HEED). The proposed algorithm shows improved result in enhancing the life time of the network in both stationary and mobile environment
Deskripsi Alternatif :Wireless Sensor Networks (WSNs) are special type of network with sensing and monitoring the physical parameters with the property of autonomous in nature. To implement this autonomy and network management the common method used is hierarchical clustering. Hierarchical clustering helps for ease access to data collection and forwarding the same to the base station. The proposed Distributed Self-organizing Load Balancing Clustering Algorithm (DSLBCA) for WSNs designed considering the parameters of neighbor distance, residual energy, and node density. The validity of the DSLBCA has been shown by comparing the network lifetime and energy dissipation with Low Energy Adaptive Clustering Hierarchy (LEACH), and Hybrid Energy Efficient Distributed Clustering (HEED). The proposed algorithm shows improved result in enhancing the life time of the network in both stationary and mobile environment
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