Hybrid approach to energy efficient clustering for heterogeneous wireless sensor network using biogeography based optimization and k-means

2019 ◽  
Vol 1 (4) ◽  
pp. 140-143
Author(s):  
Shashi BHUSHAN
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Hybrid Approach ◽  
Wireless Sensor ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering

scholarly journals Energy Efficient Clustering Protocol to Enhance Performance of Heterogeneous Wireless Sensor Network: EECPEP-HWSN

2017 ◽  
Author(s):  
Santosh Purkar ◽  
Rajkumar S. Deshpande
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Performance Parameters ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering

As Heterogeneous Wireless Sensor Network (HWSN) fulfill the requirements of researchers in the design of real life application to resolve the issues of unattended problem. But, the main constraint face by researchers is energy source available with sensor nodes. To prolong the life of sensor nodes and hence HWSN, it is necessary to design energy efficient operational schemes. One of the most suitable routing scheme is clustering approach, which improves stability and hence enhances performance parameters of HWSN. A novel solution proposed in this article is to design energy efficient clustering protocol for HWSN, to enhance performance parameters by EECPEP-HWSN. Propose protocol is designed with three level nodes namely normal, advance and super node respectively. In clustering process, for selection of cluster head we consider three parameters available with sensor node at run time, i.e., initial energy, hop count and residual energy. This protocol enhance the energy efficiency of HWSN, it improves performance parameters in the form of enhance energy remain in the network, force to enhance stability period, prolong lifetime and hence higher throughput. It is been found that proposed protocol outperforms than LEACH, DEEC and SEP with about 188, 150 and 141 percent respectively.

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 Energy Efficient Clustering Protocol to Enhance Performance of Heterogeneous Wireless Sensor Network: EECPEP-HWSN

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Santosh V. Purkar ◽  
R. S. Deshpande
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Performance Parameters ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering

Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real life application to resolve the issues of unattended problem. But, the main constraint faced by researchers is the energy source available with sensor nodes. To prolong the life of sensor nodes and thus HWSN, it is necessary to design energy efficient operational schemes. One of the most suitable approaches to enhance energy efficiency is the clustering scheme, which enhances the performance parameters of WSN. A novel solution proposed in this article is to design an energy efficient clustering protocol for HWSN, to enhance performance parameters by EECPEP-HWSN. The proposed protocol is designed with three level nodes namely normal, advanced, and super, respectively. In the clustering process, for selection of cluster head we consider different parameters available with sensor nodes at run time that is, initial energy, hop count, and residual energy. This protocol enhances the energy efficiency of HWSN and hence improves energy remaining in the network, stability, lifetime, and hence throughput. It has been found that the proposed protocol outperforms than existing well-known LEACH, DEEC, and SEP with about 188, 150, and 141 percent respectively.

scholarly journals Energy Efficient Heterogeneous WNS Clustering Using Machine Learning

2021 ◽  
pp. 24-29
Author(s):  
Kamini Maheshwar ◽  
Dr. S. Veenadhari ◽  
Mr Almelu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Heterogeneous Wireless Sensor Network ◽  
Paper Review ◽  
Energy Efficient Clustering

Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real-life application to resolve the issues of unattended problem. Wireless sensor networks are used in diverse areas such as battlefields, security, hospitals, universities, etc. It has been used in our everyday lives. Its development is rising day by day. Wireless sensor network includes hundreds to thousands of sensor nodes which aid in gathering various information like temperature, sound, location, etc. Recharging or modifying sensor nodes which might have limited battery power is usually difficult. Therefore, energy conservation is a crucial concern in sustaining the network. Clustering the networks is definitely one of the most common solutions for rendering WSNs energy. In this paper,   review and compare different energy-efficient clustering protocols for WSNs

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>

Sign in / Sign up

Export Citation Format

Share Document