An Energy Efficient Clustering Algrithm Based on DEEC Protocol and K-mean Method

2016 ◽  
Vol 3 (1) ◽  
pp. 143
Author(s):  
Elahmadi Cheikh ◽  
Chakkor Saad ◽  
Baghori Mostafa ◽  
Hajraoui Abderrahmane
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Effective Technique ◽  
New Approach ◽  
Main Research ◽  
Energy Efficient Clustering ◽  
Research Challenge ◽  
Heterogeneous Clustering

<p>In WSN the sensor nodes are usually powered by batteries and thus have very limited lifetime if no power management is performed. Because of this major limitation, energy-efficient techniques are main research challenge in this context to solve it. Dividing the network in clusters is an effective technique to achieve this goal. This algorithm is based on creating virtual sub-groups of sensor nodes in order to minimize routing calculations and to reduce the size of cluster head data aggregation. Nowadays, a lot of heterogeneous clustering protocols for WSN are created. Nevertheless, these protocols need to find the optimal clusters formation in the network that conserve CHs and theirs member nodes energy consumption. A new approach is proposed combining between an efficient clustering algorithm K-means and our proposed DEEC.  This approach has been employed to enhance DEEC protocol performances. Numerical simulation proves that the improved protocol entitled KM-DEEC achieves a satisfactory results compared to others DEEC protocol versions.</p>

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.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

2020 ◽  
Vol 17 (12) ◽  
pp. 5447-5456
Author(s):  
R. M. Alamelu ◽  
K. Prabu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Link Quality ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Energy Efficient Clustering

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

scholarly journals Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Network

2021 ◽  
Vol 13 (1) ◽  
pp. 75-92
Author(s):  
Lakshmi M ◽  
Prashanth C R
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Mac Layer ◽  
Optimum Energy ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering ◽  
Secured Data

Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.

scholarly journals WSN Clustering Based on EECI (Energy Efficient Clustering using Interconnection) Method

2019 ◽  
Vol 9 (1) ◽  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Data ◽  
Main Technique ◽  
Energy Efficient Clustering ◽  
Selection Of

in WSN, clustering gives an effective way to enhance the network lifetime. Moreover It has been observed that the clustering algorithm utilizes the two main technique first is selection of cluster head and cycling it periodically in order to distribute the energy among the clusters and this in terms increases the lifetime of network. Another challenge comes with this is minimize the energy consumption. In past several algorithm has been proposed to increase the lifetime of the network and energy consumption, however these methodologies lacks from efficiency. In this paper, we have proposed a methodologies named as EE-CI (Energy Efficient Clustering using Interconnection), along with the random updation. Here the networks are parted into different clusters, the cluster updation are done based on the CHC scheme. Moreover, in proposed methodology cluster updation and data sample is determined through the change in sensor data. Here we propose a method for sampling sensor and CHC for selecting the cluster head to balance the energy and improvise the energy efficiency. Moreover, the proposed methodology is evaluated and the result is demonstrated by considering the Leach as existing methodology, experiments results shows that the proposed methodology outperforms the existing methodology.

scholarly journals A New Energy Efficient Multitier Deterministic Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 837 ◽  
Author(s):  
Hakan Koyuncu ◽  
Geetam S. Tomar ◽  
Dinesh Sharma
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Life Span ◽  
Energy Efficient ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Primary Concern ◽  
Energy Efficient Clustering

Wireless Sensor Networks (WSNs) may be incorporated with thousands of small nodes. This gives them the capability to effectively sense, communicate, and compute parameters. However, the security and life span of a WSN node is a primary concern. This paper is focused on introducing a mathematical model of a modified Multitier Deterministic Energy-Efficient Clustering (DEC) based on novel election multi-tier random probability protocol for agricultural WSNs to enhance the life span of a WSN node along with a comparison of it with existing DEC protocol. In the proposed model, the selection of cluster heads, (CH), is done based on the energy drain pattern and location of the sensor nodes, which increased the lifespan of sensor nodes. In addition, several WSN probabilistic routing protocols to save energy throughout data transmissions like Low Energy Adaptive Clustering Hierarchy (LEACH), Power-Efficient Gathering in Sensor Information Systems (PEGASIS), DEC, and Stable Election Protocol (SEP) are explained. Moreover, it has been found that, after some mathematical modification in existing DEC routing, it will be capable to give a more positive result and reduce the energy drain in WSN nodes using a selective cluster head technique based on residual energy of sensor nodes. The DEC protocol is also compared with our proposed modified protocol for showing the energy-efficiency. The energy efficiency of clustering is associated with the field of energy sustainability of wireless sensor networks which is in the scope of Symmetry journal.

scholarly journals Implementation of Energy HEED (ER-HEED) Protocol Using Super Cluster Head for WSN

2018 ◽  
Vol 7 (S1) ◽  
pp. 119-122
Author(s):  
G. Pattabirani ◽  
K. Selvakumar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Hybrid Energy ◽  
Almost All ◽  
Energy Efficient Clustering ◽  
Super Cluster Head

Wireless Sensor Network (WSN) is used in almost all applications in developing environment. This is due to their ability and easy implementation through several applications. The most important criteria in WSN are to minimize the energy consumption and improve the network lifetime. Clustering algorithms are considered as one of the effective way to improve the network lifetime in WSN. Hybrid, Energy-Efficient and Distributed (HEED) clustering approach uses energy-efficient clustering algorithm. This paper proposes an Enhanced Rotational HEED (ER-HEED) protocol using super cluster head for minimizing energy consumption and to improve the network lifetime. The proposed work is carried out in two stages, first stage, super cluster head is introduced. In second stage, the node with maximum threshold is chosen as a cluster head on rotation within in the cluster. The results show that the ER-HEED performs well when compared with HEED and LEACH.

scholarly journals Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSN

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 627
Author(s):  
Nhat-Tien Nguyen ◽  
Thien T. T. Le ◽  
Huy-Hung Nguyen ◽  
Miroslav Voznak
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Depth Level ◽  
Large Numbers ◽  
Energy Efficient Clustering

Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption.

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