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 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.

scholarly journals EECDA: Energy Efficient Clustering and Data Aggregation Protocol for Heterogeneous Wireless Sensor Networks

2011 ◽  
Vol 6 (1) ◽  
pp. 113 ◽  
Author(s):  
Dilip Kumar ◽  
Trilok C. Aseri ◽  
R.B. Patel
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

In recent years, energy efficiency and data gathering is a major concern in many applications of Wireless Sensor Networks (WSNs). One of the important issues in WSNs is how to save the energy consumption for prolonging the network lifetime. For this purpose, many novel innovative techniques are required to improve the energy efficiency and lifetime of the network. In this paper, we propose a novel Energy Efficient Clustering and Data Aggregation (EECDA) protocol for the heterogeneous WSNs which combines the ideas of energy efficient cluster based routing and data aggregation to achieve a better performance in terms of lifetime and stability. EECDA protocol includes a novel cluster head election technique and a path would be selected with maximum sum of energy residues for data transmission instead of the path with minimum energy consumption. Simulation results show that EECDA balances the energy consumption and prolongs the network lifetime by a factor of 51%, 35% and 10% when compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy Efficient Hierarchical Clustering Algorithm (EEHCA) and Effective Data Gathering Algorithm (EDGA), respectively.

scholarly journals A Modified Energy-Efficient Clustering with Splitting and Merging for Wireless Sensor Networks using Cluster-Head Handover Mechanism

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Abdoulie M.S. Tekanyi ◽  
Jinadu A Braimoh ◽  
Buba G Bajoga
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Modified Model ◽  
Handover Mechanism ◽  
Energy Efficient Clustering

Energy efficiency is one of the most important challenges for Wireless Sensor Networks (WSNs). This is due to the fact that sensor nodes have limited energy capacity. Therefore, the energy of sensor nodes has to be efficiently managed to provide longer lifetime for the network. To reduce energy consumption in WSNs, a modified Energy Efficient Clustering with Splitting and Merging (EECSM) for WSNs using Cluster-Head Handover Mechanism was implemented in this research. The modified model used information of the residual energy of sensor nodes to select backup Cluster Heads (CHs) while maintaining a suitable CH handover threshold to minimize energy consumption in the network. The backup CHs take over the responsibilities of the CHs once the handover threshold is reached. The modified model was validated in terms of network lifetime and residual energy ratio with EECSM using MATLAB R2013a. Average improvements of 7.5% and 50.7% were achieved for the network lifetime and residual energy ratio respectively which indicates a significant reduction in energy consumption of the network nodes. Keywords— Clustering, Energy-Efficiency, Handover, Lifetime, Wireless Sensor Network

Prolonging Lifetime of Wireless Sensor Networks with Energy-Efficient Clustering Scheme

2012 ◽  
Vol 433-440 ◽  
pp. 5233-5238
Author(s):  
Behrooz Talebzadeh ◽  
Mohammad Ali Jabraeil Jamali ◽  
Mahmoud Alilou ◽  
Fahimeh Agazadeh ◽  
Ali Asghar Kavian
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Load Balance ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Optimal Cluster ◽  
Selection Of ◽  
Specific Cluster

In this paper, we will present an energy efficient clustering scheme in order to increase the wireless sensor network’s lifetime. In the proposed method all of the nodes are able to appear as cluster heads, in other words each node decides whether to act as a cluster head and aggregate data or to route the incoming data to a neighbor better suited for this role. The main goal of the proposed method is to eliminate the extensive overhead due to selection of the cluster head and the agreement on it. One of the characteristics of the proposed method is that it does not converge to a specific cluster head, so the balances the energy consumption in clusters which will result in increment the network’s lifetime. In addition the proposed method reduces the delay in the network and also maintains the load balance in a significant manner by selecting the optimal cluster head and optimal intra-cluster and outside-cluster paths.

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.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

An Energy-Efficient Clustering Algorithm Using Fuzzy C-Means and Genetic Fuzzy System for Wireless Sensor Network

2016 ◽  
Vol 26 (01) ◽  
pp. 1750004 ◽  
Author(s):  
Ayub Shokrollahi ◽  
Babak Mazloom-Nezhad Maybodi
Keyword(s):  
Energy Consumption ◽  
Fuzzy System ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Wireless Sensor ◽  
Cluster Center ◽  
Fcm Algorithm ◽  
Fuzzy C Means ◽  
Genetic Fuzzy System ◽  
Energy Efficient Clustering

The energy efficiency in wireless sensor networks (WSNs) is a fundamental challenge. Cluster-based routing is an energy saving method in this type of networks. This paper presents an energy-efficient clustering algorithm based on fuzzy c-means algorithm and genetic fuzzy system (ECAFG). By using FCM algorithm, the clusters are formed, and then cluster heads (CHs) are selected utilizing GFS. The formed clusters will be remaining static but CHs are selected at the beginning of each round. FCM algorithm forms balanced clusters and distributes the consumed energy among them. Using static clusters also reduces the data overhead and consequently the energy consumption. In GFS, nodes energy, the distance from nodes to the base station and the distance from each node to its corresponding cluster center are considered as determining factors in CHs selection. Then, genetic algorithm is also used to obtain fuzzy if–then rules of GFS. Consequently, the system performance is improved and appropriate CHs can be selected, hence energy dissipation is reduced. The simulation results show that ECAFG, compared with the existing methods, significantly reduces the energy consumption of the sensor nodes, and prolongs the network lifetime.

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