scholarly journals Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

2018 ◽  
Vol 9 (4) ◽  
Author(s):  
Abhilasha Jain ◽  
Ashok Kumar
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Efficient Algorithm ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering

A Hybrid Approach of Fuzzy C-means Clustering and Neural network to make Energy-Efficient heterogeneous Wireless Sensor network

2016 ◽  
Vol 6 (2) ◽  
pp. 674 ◽  
Author(s):  
Amit Kumar Kaushik
Keyword(s):  
Neural Network ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Hybrid Approach ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Heterogeneous Wireless Sensor Network ◽  
Fuzzy C Means Clustering

<span>The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature. </span>

scholarly journals A Hybrid Approach of Fuzzy C-means Clustering and Neural network to make Energy-Efficient heterogeneous Wireless Sensor network

2016 ◽  
Vol 6 (2) ◽  
pp. 674
Author(s):  
Amit Kumar Kaushik
Keyword(s):  
Neural Network ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Hybrid Approach ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy C Means ◽  
Heterogeneous Wireless Sensor Network ◽  
Fuzzy C Means Clustering

<span>The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature. </span>

The Method to Diminish Data Delivered by Sensor in Wireless Sensor Network

2011 ◽  
Vol 403-408 ◽  
pp. 2791-2794
Author(s):  
Xiang Li Liu ◽  
Zan Li ◽  
Jiang Bo Si ◽  
Ben Jian Hao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Efficient Algorithm ◽  
Energy Efficient ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Affine Transform ◽  
Energy Constraints

Severe energy constraints and limited computing abilities of the nodes in a network present a major challenge in the design and deployment of a wireless sensor network. This thesis aims to present energy efficient algorithm for data delivery in a sensor network. The methodology of data delivery presented in this thesis is based on affine transform and performs coordination compression. Experimental results show that the algorithm can reduce about half of the data amount delivered by the sensor.

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