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 Cluster-Based Routing Approach in Hierarchical Wireless Sensor Networks toward Energy Efficiency using Genetic Algorithm

2020 ◽  
Vol 30.8 (147) ◽  
pp. 14-21
Author(s):  
Thanh Huong Nguyen ◽  
◽  
Dang Toan Dao ◽  
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Architecture

Energy efficiency is one of the important factors when exploiting Wireless Sensor Networks, especially for increasing lifespan and performance. In the network nowadays, the number of sensor nodes can reach hundreds or thousands and can be arranged in complex hierarchical architecture. Besides, the current sensor nodes have a small size, limited battery source but are operated in vast areas. The clustered-based method has been an effective and potentially extensible means of boosting the management and operation of such large-scale networks and minimizing the overall energy consumption. In this paper, the issue of arranging and routing the nodes in the sensor network in a hierarchical manner is investigated, in which each lowest level sensor nodes are grouped in a cluster with a common cluster head, then the cluster-head plays an intermediate role transmit the information back and forth between the sensor nodes and the base station. In this way, the route to exchange information can not only be optimized with respect to the distance but also for energy spent on the communication. In order to do so, this paper proposed a novel method based on a Genetic Algorithm to establish a routing protocol to achieve energy optimization. The results demonstrate that this approach can decrease the energy consumption according to the optimized routing through clustering and increase the performance superior to the other clustering schemes.

A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

2020 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Dimitris N. Kanellopoulos ◽  
Pratik Gite
Keyword(s):  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Signal Power ◽  
Aggregated Data ◽  
Simulation Results ◽  
Buffer Length ◽  
Energy Buffer

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH.

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 Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Asis Kumar Tripathy ◽  
Suchismita Chinara
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Architecture ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness

Wireless sensor network swears an exceptional fine-grained interface between the virtual and physical worlds. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. Each clustering algorithm is composed of three phases cluster head (CH) selection, the setup phase, and steady state phase. The hot point in these algorithms is the cluster head selection. The focus, however, has been given to the residual energy-based clustering protocols which might differ depending on the application and network architecture. In this paper, a survey of the state-of-the-art clustering techniques in WSNs has been compared to find the merits and demerits among themselves. It has been assumed that the sensor nodes are randomly distributed and are not mobile, the coordinates of the base station (BS) and the dimensions of the sensor field are known.

Design of Hybridized Wireless Sensor Network using K-Means Clustering and Genetic Algorithm

2017 ◽  
Vol 2 (5) ◽  
pp. 1-6
Author(s):  
M. D. Gbolagade ◽  
R. G. Jimoh ◽  
K. A. Gbolagade ◽  
O. V. Mejabi
Keyword(s):  
Data Transfer ◽  
Cluster Head ◽  
Simulated Data ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Cluster Heads ◽  
Main Challenge

Prolonging the network lifetime in wireless sensor networks (WSNs), Clustering has been recognized has one of the significant methods in achieving this, It entails grouping of sensor nodes into clusters and electing cluster heads (CHs) for all the clusters. CH’s accept data from relevant cluster’s nodes and forward the aggregate data to base station. A main challenge in WSNs is the selection of appropriate cluster heads. This work proposes a system that is efficient, scalable and load balanced. The proposed scheme combines two known algorithms namely k-means clustering and genetic algorithms based on the weaknesses identified in the two. The simulated data is obtained through the enhancement of clustering by the cluster head (base station) that helps in locating the nearest node that is important in the data transfer instead of transferring to a node that is not necessary, thereby wasting time and resources. The obtained simulation results indicate that this approach is efficient and last longer in elongating the battery life time than the conventional method by 60%.

Distance Based Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

2014 ◽  
Vol 626 ◽  
pp. 20-25
Author(s):  
K. Kalaiselvi ◽  
G.R. Suresh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Energy Efficient Routing

In wireless sensor networks Energy-efficient routing is an important issue due to the limited battery power within the network, Energy consumption is one of the important performance factors. Specifically for the election of cluster head selection and distance between the cluster head node and base station. The main objective of this proposed system is to reduce the energy consumption and prolong the network lifetime. This paper introduces a new clustering algorithm for energy efficient routing based on a cluster head selection

Research and Improvement about LEACH Algorithm for Wireless Sensor Networks

2014 ◽  
Vol 599-601 ◽  
pp. 1954-1959
Author(s):  
Tao Liu ◽  
Sui Min Jia
Keyword(s):  
Clustering Algorithm ◽  
Cluster Head ◽  
Premature Death ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Cluster Number ◽  
Local Data ◽  
Distance Threshold ◽  
Energy Distance

In Wireless Sensor Network (WSN), unreasonable node clustering algorithm will inevitably lead to premature death, unawareness of regional information.To address problems of traditional LEACH algorithm, An improved LEACH multi-hop routing algorithm based on Energy Distance Threshold (EDT) is presented. It mainly improves from aspects of cluster number, cluster head selection and inter-cluster communication. The improved clustering hierarchy algorithm considers the nodes Energy Distance Threshold as an important factor in selection then chooses the best cluster head within the area. The selection of cluster head is based on re-select manner, which dynamically and effectively select cluster heads by control cluster number and combing with EDT. After cluster head completes local data fusion and processing, it look for adjacent cluster head as next hop closer to base station with larger EDT if the head is far away from station. The next hop repeats above process till the base station is arrived. Such manner of multi-hop among clusters enables communication among clusters and base stations so as to avoid direct communication between head and station. The method reduces energy consumption and also balances energy. Simulation results show the improved LEACH algorithm has higher energy utilizing rate, and it helps prolong network’s lifetime.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5228-5232
Author(s):  
Mohammad Ahmadi ◽  
Hamid Faraji ◽  
Hossien Zohrevand
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

scholarly journals Firefly Algorithm Solution to Improving Threshold Distributed Energy Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks

2017 ◽  
Vol 6 (3) ◽  
pp. 91
Author(s):  
Baghouri Mostafa ◽  
Chakkor Saad ◽  
Hajraoui Abderrahmane
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Firefly Algorithm ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Single Node ◽  
Heterogeneous Wireless Sensor Networks ◽  
Energy Efficient Clustering

The improvement of the lifetime of heterogeneous wireless sensor networks is a challenge for many researches. One of the most important protocols to achieve this goal is to divide the network into clusters that run by a single node called cluster head and the others have attached. However, all nodes must form the cluster including the nearest nodes to the base station which should be excluded from the clustering process. Furthermore these nodes consume more energy since each member node communicates directly with their cluster head and not with the base station. To eliminate these notes from cluster process, we need to formulate a new energy total of the network which depends on the number of these nodes. In this paper we propose a new technic to optimize this energy which basing on the firefly algorithm. The developed approach allows the boundary of the excluded nodes efficiently. Computer simulation in MATLAB proves the superiority of this method concerning the increase of the lifetime and the number of the received packet messages compared to the others protocols.

New Routing Technique to Enhance Energy Efficiency and Maximize Lifetime of the Network in WSNs

2020 ◽  
Vol 9 (2) ◽  
pp. 81-93
Author(s):  
Nezha El Idrissi ◽  
Abdellah Najid ◽  
Hassan El Alami
Keyword(s):  
Energy Efficiency ◽  
Energy Conservation ◽  
Network Lifetime ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Save Energy ◽  
Selection Of

Energy conservation plays a role important in wireless sensor network (WSN) design. The technique of clustering is one of the approaches to save energy of WSNs; several protocols based on the clustering technique are proposed in the context of energy conservation and maximization of network lifetime. This article proposed a new routing technique to maximize the network lifetime and enhance energy efficiency in WSNs, namely optimal selection of cluster head in the grid (OSCH-Gi). This technique divides the network area into a clustered grid. Each clustered grid has a cluster head (CH) it has been chosen based on the residual energy and distance to the base station of each node. Simulation results indicate that the proposed technique is more effective than other clustering algorithms in terms of the network lifetime and energy consumption.

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