scholarly journals Authenticated Energy Efficient Clustering Algorithm for secure transmission in Wireless Sensor Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 111-116
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Complex Structure ◽  
Data Communication ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

Authenticated energy consumption is the main criteria for constructing the Wireless Sensor Networks (WSNs). Every sensor has the dissimilar processing, communication range, memory unit. Each sensor node has restricted energy and memory. All the WSN based transmission architecture has the problem of authentication. The transmission overload and energy utilization have complex structure to perform the quality of service in WSN routing in a secure way. In spite of providing efficient communication for WSN, clustering approach is used to transmit the data packet from beginning node to the end node. Data gathering helps to organize the network and minimize the network overhead during data communication. Effective cluster head selection method is used for enhanced energy efficiency. Authenticated Energy Efficient Clustering Algorithm (AEEC) is proposed for efficient authenticated energy consumption-based routing methodology for WSN. The effective communication is performed by generating the authentication code within the sensor nodes to construct the innovative secured transmission based framework. The simulation results proved that the proposed method is implemented to reduce the energy consumption, routing overhead, end to end delay and increased amount of throughput compared to the other techniques.

Efficient Energy Conservation and Faulty Node Detection on Machine Learning-Based Wireless Sensor Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 1-20
Author(s):  
Amarasimha T. ◽  
V. Srinivasa Rao
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Communication ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Faulty Node

Wireless sensor networks are used in machine learning for data communication and classification. Sensor nodes in network suffer from low battery power, so it is necessary to reduce energy consumption. One way of decreasing energy utilization is reducing the information transmitted by an advanced machine learning process called support vector machine. Further, nodes in WSN malfunction upon the occurrence of malicious activities. To overcome these issues, energy conserving and faulty node detection WSN is proposed. SVM optimizes data to be transmitted via one-hop transmission. It sends only the extreme points of data instead of transmitting whole information. This will reduce transmitting energy and accumulate excess energy for future purpose. Moreover, malfunction nodes are identified to overcome difficulties on data processing. Since each node transmits data to nearby nodes, the misbehaving nodes are detected based on transmission speed. The experimental results show that proposed algorithm provides better results in terms of reduced energy consumption and faulty node detection.

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