scholarly journals FLECH: Fuzzy Logic Based Energy Efficient Clustering Hierarchy for Nonuniform Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Baranidharan Balakrishnan ◽  
Santhi Balachandran
Keyword(s):  
Fuzzy Logic ◽  
Data Collection ◽  
Data Transmission ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Redundant Data ◽  
Energy Efficient Clustering

Lifetime of Wireless Sensor Network (WSN) is an important issue which affects its implementation in various real time applications. The major factor behind the energy consumption in WSN is its data collection mechanism. The direct data transmission from each sensor node to the Base Station (BS) consumes more energy than other alternatives. Also it is unnecessary, due to redundant data transmission because of geographically closer nodes. Clustering is the best data collection architectural model for WSN since it takes care of in-network processing which handles redundant data within the network. The techniques used for the network having uniform node distribution are not suitable for the networks which have nonuniformly distributed nodes. This paper contributes a novel clustering algorithm: Fuzzy Logic Based Energy Efficient Clustering Hierarchy (FLECH) for nonuniform WSN. The clusters in FLECH are created using proper parameters which increases the lifetime of the WSN. Fuzzy logic in FLECH is wisely used to combine important parameters like residual energy, node centrality, and distance to BS for electing best suitable nodes as CH and increases the network lifetime. FLECH performance is verified in different scenarios and the results are compared with LEACH, CHEF, ECPF, EAUCF, and MOFCA. The simulation results clearly indicate the lifetime increase by FLECH over other algorithms and its energy conservation per round of data collection in the network.

scholarly journals Clustering Algorithm for Energy- Efficient Wireless Sensor Network

2021 ◽  
Vol 12 (5) ◽  
pp. 877-884
Author(s):  
Asha Rawat, Dr. Mukesh Kalla
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Packet Transmission ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more efficiently extends the life of the wireless sensor network. The algorithm prolongs the life and effectiveness of the Wireless Sensor Network.

scholarly journals DHCFL: Dual Head Clustering Based on Fuzzy Logic for Wireless Sensor Networks

2020 ◽  
Vol 8 (5) ◽  
pp. 1049-1054
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Data Transmission ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Research Work ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless Sensor Networks (WSN) are constructed by interconnecting miniature sensor nodes for monitoring the environment uninterrupted. These miniature nodes are having the sensing, processing and communication capability in a smaller scale powered by a battery unit. Proper energy conservation is required for the entire system. Clustering mechanism in WSN advances the lifetime and stability in the network. It achieves data aggregation and reduces the number of data transmission to the Base station (BS). But the Cluster Head (CH) nodes are affected by rapid energy depletion problem due to overload. A CH node spends its energy for receiving data from its member nodes, aggregation and transmission to the BS. In CH election, multiple overlapping factors makes it difficult and inefficient which costs the lifetime of the network. In recent years, Fuzzy Logic is widely used for CH election mechanism for WSN. But the underlying problem of the CHs node continues. In this research work, a new clustering algorithm DHCFL is proposed which elects two CHs for a cluster which shares the load of a conventional CH node. Data reception and aggregation will be done by CH aggregator (CH-A) node and data transmission to the BS will be carried over by CH relay (CH-R) node. Both CH-A and CH-R nodes are elected through fuzzy logic which addresses the uncertainty in the network too. The proposed algorithm DHCFL is compared and tested in different network scenarios with existing clustering algorithms and it is observed that DHCFL outperforms other algorithms in all the network scenarios.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

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