scholarly journals An Improved Routing Schema with Special Clustering Using PSO Algorithm for Heterogeneous Wireless Sensor Network

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 671 ◽  
Author(s):  
Jin Wang ◽  
Yu Gao ◽  
Wei Liu ◽  
Arun Sangaiah ◽  
Hye-Jin Kim
Keyword(s):  
Energy Efficiency ◽  
Clustering Algorithm ◽  
Pso Algorithm ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Energy Balancing ◽  
Research Issues ◽  
Protection Mechanism ◽  
Clustering Problem ◽  
Heterogeneous Wireless Sensor Network

Energy efficiency and energy balancing are crucial research issues as per routing protocol designing for self-organized wireless sensor networks (WSNs). Many literatures used the clustering algorithm to achieve energy efficiency and energy balancing, however, there are usually energy holes near the cluster heads (CHs) because of the heavy burden of forwarding. As the clustering problem in lossy WSNs is proved to be a NP-hard problem, many metaheuristic algorithms are utilized to solve the problem. In this paper, a special clustering method called Energy Centers Searching using Particle Swarm Optimization (EC-PSO) is presented to avoid these energy holes and search energy centers for CHs selection. During the first period, the CHs are elected using geometric method. After the energy of the network is heterogeneous, EC-PSO is adopted for clustering. Energy centers are searched using an improved PSO algorithm and nodes close to the energy center are elected as CHs. Additionally, a protection mechanism is also used to prevent low energy nodes from being the forwarder and a mobile data collector is introduced to gather the data. We conduct numerous simulations to illustrate that our presented EC-PSO outperforms than some similar works in terms of network lifetime enhancement and energy utilization ratio.

scholarly journals GENETIC ALGORITHM-BASED CLUSTERING OF WIRELESS SENSOR NETWORK WITH NOVEL DATA ENCRYPTION

2017 ◽  
Vol 10 (13) ◽  
pp. 94
Author(s):  
Bachujayendra Kumar ◽  
Rajya Lakshmidevi K ◽  
M Verginraja Sarobin
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Information Security ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Data Encryption ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Techniques ◽  
Main Challenge

Wireless sensor networks (WSNs) have been used widely in so many applications. It is the most efficient way to monitor the information. There areso many ways to deploy the sensors. Many problems are not identified and solved. The main challenge of WSN is energy efficiency and information security. WSN power consumption is reduced by genetic algorithm-based clustering algorithm. Information from cluster head to base station may have a lot of chances to get hacked. The most reliable way to manage energy consumption is clustering, and encryption will suit best for information security. In this paper, we explain clustering techniques and a new algorithm to encrypt the data in the network.

scholarly journals Novel Scheme for Minimal Iterative PSO Algorithm for Extending Network Lifetime of Wireless Sensor Network

2018 ◽  
Vol 8 (2) ◽  
pp. 1084
Author(s):  
Hemavathi P ◽  
Nandakumar A. N.
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Dynamic Network ◽  
Cost Effective ◽  
Pso Algorithm ◽  
Wireless Sensor ◽  
Cost Effective Method ◽  
Significant Research

Clustering is one of the operations in the wireless sensor network that offers both streamlined data routing services as well as energy efficiency. In this viewpoint, Particle Swarm Optimization (PSO) has already proved its effectiveness in enhancing clustering operation, energy efficiency, etc. However, PSO also suffers from a higher degree of iteration and computational complexity when it comes to solving complex problems, e.g., allocating transmittance energy to the cluster head in a dynamic network. Therefore, we present a novel, simple, and yet a cost-effective method that performs enhancement of the conventional PSO approach for minimizing the iterative steps and maximizing the probability of selecting a better clustered. A significant research contribution of the proposed system is its assurance towards minimizing the transmittance energy as well as receiving energy of a cluster head. The study outcome proved proposed a system to be better than conventional system in the form of energy efficiency.

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 ANCAEE: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

2011 ◽  
Vol 03 (09) ◽  
pp. 307-312 ◽  
Author(s):  
A. P. Abidoye ◽  
N. A. Azeez ◽  
A. O. Adesina ◽  
K. K. Agbele
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Wireless Sensor

scholarly journals 3D GEO-CLUSTERING FOR WIRELESS SENSOR NETWORK IN SMART CITY

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 11-16 ◽  
Author(s):  
S. Azri ◽  
U. Ujang ◽  
A. Abdul Rahman
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Smart City ◽  
Clustering Algorithm ◽  
Smart Cities ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Social Infrastructure ◽  
Head Node

<p><strong>Abstract.</strong> Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance.</p>

scholarly journals An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
C. Vimalarani ◽  
R. Subramanian ◽  
S. N. Sivanandam
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Performance Metrics ◽  
Energy Optimization ◽  
Pso Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area ◽  
Energy Conservation Measures

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

Proficient Clustering algorithm for Wireless Sensor Networks

2020 ◽  
pp. 249-261
Author(s):  
Nivetha Gopal ◽  
Venkatalakshmi Krishnan
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Algorithm ◽  
Clustering Algorithm ◽  
Fruit Fly ◽  
Wireless Sensor ◽  
Fruit Fly Optimization Algorithm ◽  
Matlab Simulation ◽  
Fruit Fly Optimization

Enhancing the energy efficiency and maximizing the networking lifetime are the major challenges in Wireless Sensor Networks (WSN).Swarm Intelligence based algorithms are very efficient in solving nonlinear design problems with real-world applications.In this paper a Swarm based Fruit Fly Optimization Algorithm (FFOA) with the concept of K-Medoid clustering and swapping is implemented to increase the energy efficiency and lifetime of WSN. A comparative analysis is performed in terms of cluster compactness,cluster error and convergence. MATLAB Simulation results show that K-Medoid Swapping and Bunching Fruit Fly optimization (KMSB-FFOA) outperforms FFOA and K-Medoid Fruit Fly Optimization Algorithm (KM-FFOA).

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.

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