Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
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Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
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Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
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Blockchain Framework for Communication between Vehicle through IoT Devices and Sensors
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Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
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A Review on Data Securing Techniques using Internet of Medical Things
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Machine Learning Algorithms Performance Analysis for VLSI IC Design
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Maximizing the Prediction Accuracy in Tweet Sentiment Extraction using Tensor Flow based Deep Neural Networks
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Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
DDOS ATTACK DETECTION IN TELECOMMUNICATION NETWORK USING MACHINE LEARNING
Volume-1 | Issue-1
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
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Construction of a Framework for Selecting an Effective Learning Procedure in the School-Level Sector of Online Teaching Informatics
Volume-3 | Issue-4
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Characterizing WDT subsystem of a Wi-Fi controller in an Automobile based on MIPS32 CPU platform across PVT
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Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
Design of Data Mining Techniques for Online Blood Bank Management by CNN Model
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Ethereum and IOTA based Battery Management System with Internet of Vehicles
Volume-3 | Issue-3
Volume - 2 | Issue - 4 | december 2020
Published
12 January, 2021
A typical Wireless Sensor Network (WSN) comprises of multiple nodes that are used to control as well as monitor the environment and perform pre-described actions. Based on the network, the sensor nodes are distributed and their energy consumption proves to be challenging. When the nodes are located near the sink, they serve as the interface for data transfer between the sink and the node. Because of this, there is a decrease in the networks lifetime and further the energy consumption of the nodes increases significantly. Denial-of-sleep attack is a threat that sensor nodes face in WSNs. DoSA is the condition when there is much loss of energy at the nodes by preventing them from entering into sleep mode and power save mode. We propose a hybrid methodology of Hopfield neural network and firefly algorithm using leach to tackle this issue such that there is a significant increase in network lifetime and energy consumption patterns.
KeywordsWireless Sensor networks Hopfield neural network Firefly algorithm denial-of-sleep attack Hybrid algorithm
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