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

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 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 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.

A Reliable Energy Efficient Wireless Sensor Network Hierarchical Routing Algorithm

2013 ◽  
Vol 475-476 ◽  
pp. 569-572
Author(s):  
Kai Guo Qian ◽  
Lin Ou
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Hierarchical Routing

The existing clustering protocols exists shortages that the nodes with small residual energy may be choose as cluster nodes, which communicate directly with sink causes more energy consumption. Member nodes transmit data directly to cluster head also caused more energy consumption. A reliable energy efficient wireless sensor network hierarchical routing algorithm (REHRA) is proposed to further improve energy efficiency. It introduces residual energy factor for election of heads that makes nodes with more residual energy priority become heads. The data transmission for heads to sink uses flooding algorithm that ensures reliability. Routing tree is formed within local cluster and data delivers from leaf nodes to the cluster head. Performance analysis and simulation experiment shows that the new algorithm provides higher energy efficiency and longer lifetime.

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.

Energy Efficient Multi-Hop Wireless Sensor Networks with CMIMO-SM Scheme

2014 ◽  
Vol 666 ◽  
pp. 322-326
Author(s):  
Yu Yang Peng ◽  
Jae Ho Choi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Improve Energy Efficiency ◽  
Output System

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.

A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

2015 ◽  
Vol 785 ◽  
pp. 744-750
Author(s):  
Lei Gao ◽  
Qun Chen
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Selection Criterion ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

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 Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks Based on Yellow Saddle Goatfish Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1515 ◽  
Author(s):  
Alma Rodríguez ◽  
Carolina Del-Valle-Soto ◽  
Ramiro Velázquez
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Structure ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Energy Efficient Clustering

The usage of wireless sensor devices in many applications, such as in the Internet of Things and monitoring in dangerous geographical spaces, has increased in recent years. However, sensor nodes have limited power, and battery replacement is not viable in most cases. Thus, energy savings in Wireless Sensor Networks (WSNs) is the primary concern in the design of efficient communication protocols. Therefore, a novel energy-efficient clustering routing protocol for WSNs based on Yellow Saddle Goatfish Algorithm (YSGA) is proposed. The protocol is intended to intensify the network lifetime by reducing energy consumption. The network considers a base station and a set of cluster heads in its cluster structure. The number of cluster heads and the selection of optimal cluster heads is determined by the YSGA algorithm, while sensor nodes are assigned to its nearest cluster head. The cluster structure of the network is reconfigured by YSGA to ensure an optimal distribution of cluster heads and reduce the transmission distance. Experiments show competitive results and demonstrate that the proposed routing protocol minimizes the energy consumption, improves the lifetime, and prolongs the stability period of the network in comparison with the stated of the art clustering routing protocols.

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