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Journal of IoT in Social, Mobile, Analytics, and Cloud

Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3

Design of Deep Learning Algorithm for IoT Application by Image based Recognition
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Analysis of Serverless Computing Techniques in Cloud Software Framework
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Health Record Management System – A Web-based Application
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A Novel Signal Processing Based Driver Drowsiness Detection System
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IoT Based Monitoring and Control System using Sensors
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Secure Data Sharing Platform for Portable Social Networks with Power Saving Operation
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Review of Internet of Wearable Things and Healthcare based Computational Devices
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Stock Index Prediction with Financial News Sentiments and Technical Indicators
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Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs
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Suspicious Human Activity Detection System
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ROBOT ASSISTED SENSING, CONTROL AND MANUFACTURE IN AUTOMOBILE INDUSTRY
Volume-1 | Issue-3

EFFICIENT RESOURCE ALLOCATION AND QOS ENHANCEMENTS OF IOT WITH FOG NETWORK
Volume-1 | Issue-2

Live Streaming Architectures for Video Data - A Review
Volume-2 | Issue-4

IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2

Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3

A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3

IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS
Volume-2 | Issue-1

Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3

Hybrid Intrusion Detection System for Internet of Things (IoT)
Volume-2 | Issue-4

Home / Archives / Volume-3 / Issue-1 / Article-5

Volume - 3 | Issue - 1 | march 2021

Enhanced Dragonfly Algorithm based K-Medoid Clustering Model for VANET
Pages: 50-59
Published
07 April, 2021
Abstract

A VANET or vehicular Ad Hoc Network is known for its fast topology transition and node mobility, contributing to its attributes as an ad hoc network. The aspect of gathering the nodes, making this system extremely vigorous is known as clustering. However, in certain cases, it is not possible to keep track of the nodes which will results in network issues due to energy insufficiency during execution. Hence this will lead to primary energy management problems faced during the routing protocol which take into consideration the node lifetime. To address this discrepancy, we have proposed a novel optimization technique based on clustering. It has been observed that the proposed methodology will further improve the effectiveness of V2V communication. In this paper, clustering of the vehicle nodes is done using K-Medoid clustering model and are then used to improve energy efficiency. A metaheuristic algorithm is used to establish an energy efficient communication methodology. Based on the simulation analysis performed, it is seen that this methodology requires lesser execution time and improves the nodes' energy efficiency.

Keywords

VAENT EDA algorithm energy efficient routing protocol V2V communication metaheuristic algorithm

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