scholarly journals Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols

2021 ◽  
Vol 11 (23) ◽  
pp. 11448
Author(s):  
Ahmed Mahdi Jubair ◽  
Rosilah Hassan ◽  
Azana Hafizah Mohd Aman ◽  
Hasimi Sallehudin ◽  
Zeyad Ghaleb Al-Mekhlafi ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Optimization Methods ◽  
Base Station ◽  
Optimization Techniques ◽  
Wireless Sensor ◽  
Small Scale ◽  
Network Clustering ◽  
Head Node ◽  
Clustering Protocols ◽  
Clustering Optimization

Recently, Wireless Sensor Network (WSN) technology has emerged extensively. This began with the deployment of small-scale WSNs and progressed to that of larger-scale and Internet of Things-based WSNs, focusing more on energy conservation. Network clustering is one of the ways to improve the energy efficiency of WSNs. Network clustering is a process of partitioning nodes into several clusters before selecting some nodes, which are called the Cluster Heads (CHs). The role of the regular nodes in a clustered WSN is to sense the environment and transmit the sensed data to the selected head node; this CH gathers the data for onward forwarding to the Base Station. Advantages of clustering nodes in WSNs include high callability, reduced routing delay, and increased energy efficiency. This article presents a state-of-the-art review of the available optimization techniques, beginning with the fundamentals of clustering and followed by clustering process optimization, to classifying the existing clustering protocols in WSNs. The current clustering approaches are categorized into meta-heuristic, fuzzy logic, and hybrid based on the network organization and adopted clustering management techniques. To determine clustering protocols’ competency, we compared the features and parameters of the clustering and examined the objectives, benefits, and key features of various clustering optimization methods.

scholarly journals Estimation of Optimum Rendezvous Point for Mobile Sink (ORP-MS) in WSN

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1322 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav J Nigam
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
High Throughput ◽  
Mobile Sink ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Rendezvous Point ◽  
Coverage Holes

Clustering of the sensors in wireless sensor network is done to achieve energy efficiency. The nodes, which are unable to join any cluster, are referred to as isolated nodes and tend to transfer information straight to the base station. It is palpable that isolated nodes and cluster heads communicate with the base station and tend to exhaust their energy leaving behind coverage holes. In this paper, we propose the innovative clustering scheme using mobile sink approach to extend networks lifetime. The proposed (ORP-MS) algorithm is implemented in MATLAB 2017a and the results revealed that the proposed algorithm outdid the existing algorithms in terms networks lifetime and energy efficiency simultaneously achieved high throughput.  

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.

Estimation of Secured Wireless Sensor Networks and Its Significant Observation for Improving Energy Efficiency Using Cross-Learning Algorithms

2021 ◽  
pp. 450-467
Author(s):  
Sirasani Srinivasa Rao ◽  
K. Butchi Raju ◽  
Sunanda Nalajala ◽  
Ramesh Vatambeti
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Learning Algorithms ◽  
Base Station ◽  
Wireless Sensor ◽  
Control Applications ◽  
Symmetric Key ◽  
And Control ◽  
The Ideal

Wireless sensor networks (WSNs) have as of late been created as a stage for various significant observation and control applications. WSNs are continuously utilized in different applications, for example, therapeutic, military, and mechanical segments. Since the WSN is helpless against assaults, refined security administrations are required for verifying the information correspondence between hubs. Because of the asset limitations, the symmetric key foundation is considered as the ideal worldview for verifying the key trade in WSN. The sensor hubs in the WSN course gathered data to the base station. Despite the fact that the specially appointed system is adaptable with the variable foundation, they are exposed to different security dangers. Grouping is a successful way to deal with vitality productivity in the system. In bunching, information accumulation is utilized to diminish the measure of information that streams in the system.

SGO A New Approach for Energy Efficient Clustering in WSN

2018 ◽  
Vol 7 (3) ◽  
pp. 54-72 ◽  
Author(s):  
Pritee Parwekar
Keyword(s):  
Energy Efficient ◽  
Base Station ◽  
Optimization Techniques ◽  
Wireless Sensor ◽  
New Approach ◽  
Transmission Distance ◽  
Np Hard Problem ◽  
Communication Distance ◽  
Social Group Optimization ◽  
Energy Efficient Clustering

In wireless sensor networks (WSNs), consumption of energy is the major challenging issue. If the data is transmitted directly from the node to the base station, it leads to more transmissions and energy consumed also increases if the communication distance is longer. In such cases, to reduce the longer communication distances and to reduce the number of transmissions, a clustering technique is employed. Another way to reduce the energy consumed is to reduce the transmission from node to CH or from CH to BS. Reducing the transmission distance is a NP-Hard problem. So, optimization techniques can be used effectively to solve such problems. In this article, is the implementation of a social group optimization (SGO) to reduce the transmission distance and to allow the nodes to consume less energy. The performance of SGO is compared with GA and PSO and the results show that SGO outperforms in terms of fitness and energy.

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.

DATA MINING VIA MINIMAL SPANNING TREE CLUSTERING FOR PROLONGING LIFETIME OF WIRELESS SENSOR NETWORKS

2007 ◽  
Vol 06 (02) ◽  
pp. 235-251 ◽  
Author(s):  
GUANGYAN HUANG ◽  
XIAOWEI LI ◽  
JING HE ◽  
XIN LI
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spanning Tree ◽  
Base Station ◽  
Wireless Sensor ◽  
Evaluation Metrics ◽  
Minimal Spanning Tree ◽  
Clustering Methods

Clustering is applied in wireless sensor networks for increasing energy efficiency. Clustering methods in wireless sensor networks are different from those in traditional data mining systems. This paper proposes a novel clustering algorithm based on Minimal Spanning Tree (MST) and Maximum Energy resource on sensors named MSTME. Also, specified constrains of clustering in wireless sensor networks and several evaluation metrics are given. MSTME performs better than already known clustering methods of Low Energy Adaptive Clustering Hierarchy (LEACH) and Base Station Controlled Dynamic Clustering Protocol (BCDCP) in wireless sensor networks when they are evaluated by these evaluation metrics. Simulation results show MSTME increases energy efficiency and network lifetime compared with LEACH and BCDCP in two-hop and multi-hop networks, respectively.

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 Improved Leach Algorithm Based on Wireless Sensor Networks

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1623-1628
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Base Station ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Current Generation ◽  
Cluster Heads ◽  
Computation Algorithm ◽  
Stable Election Protocol

In our current generation, wireless sensor network is much in use and has become quintessential. With wide improvement of technology and the various ranges developed in communication and in other aspects, this document mainly focuses on the LEACH algorithm (Adaptive Low Energy Hierarchy) and the second most important methodology used is the SEP (stable election protocol). We have discovered improvements in energy efficiency by comparing our results with these two algorithms and the sensor mortality rate is reduced to a greater extent. This research proposes an improved computation algorithm method for the calculation of LEACH clustering, by considering the importance of the cluster heads and the sensor nodes present, T (n) is reorganisedrecommendinga procedure that focuses on reducing the energy consumption. The combined rate of information is found by allowing cluster heads to gather information before it is sent to base station. This improved computation algorithmwill be able to increase vital utilisation of networks and increase sensor life.

Energy Consumption Analysis of Secure and Clustered Wireless Sensor Network

2014 ◽  
Vol 5 (1) ◽  
pp. 15-36 ◽  
Author(s):  
Ashim Pokharel ◽  
Ethiopia Nigussie
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Aggregation ◽  
Secure Communication ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Design Strategies

Due to limited energy resources, different design strategies have been proposed in order to achieve better energy efficiency in wireless sensor networks, and organizing sensor nodes into clusters and data aggregation are among such solutions. In this work, secure communication protocol is added to clustered wireless sensor network. Security is a very important requirement that keeps the overall system usable and reliable by protecting the information in the network from attackers. The proposed and implemented AES block cipher provides confidentiality to the communication between nodes and base station. The energy efficiency of LEACH clustered network and with added security is analyzed in detail. In LEACH clustering along with the implemented data aggregation technique 48% energy has been saved compared to not clustered and no aggregation network. The energy consumption overhead of the AES-based security is 9.14%. The implementation is done in Contiki and the simulation is carried out in Cooja emulator using sky motes.

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