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
Volume-3 | Issue-3
Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3
Health Record Management System – A Web-based Application
Volume-3 | Issue-4
A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3
IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2
Secure Data Sharing Platform for Portable Social Networks with Power Saving Operation
Volume-3 | Issue-3
Review of Internet of Wearable Things and Healthcare based Computational Devices
Volume-3 | Issue-3
Stock Index Prediction with Financial News Sentiments and Technical Indicators
Volume-4 | Issue-3
Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs
Volume-3 | Issue-3
Suspicious Human Activity Detection System
Volume-2 | Issue-4
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
Volume - 1 | Issue - 1 | june 2019
Published
June, 2019
The internet of things is a group of connected computing, digital and mechanical machines with the capability of being identified by other devices that are internet enabled. The wireless sensor networks is a gathering of sovereign sensing elements in combination with actuating, computing, communicating and energy storing devices to keep track of the continuous physical world changes. These clique of independent sensors that commune wirelessly incurring advantages such as low cost, limited power consumption, high scalability with adaptableness to hostile and harsh environments afford them to be connected with IOT to become a part of it, to trace the physical changes encountered in the things that are internet enabled. The conventional methods for connection establishment between WSNs with IOT are more energy consuming and prone to failures in terms of network life time, packet delivery ratio and delay. So the proposed methodology that uses the concatenation of clustering with neural and simple fuzzy rule based system supported by the shortest route determination to provide with an energy efficient and enhanced routing capabilities for IOT with WSNs ensures to have a route entrenchment with reduced power consumption and improvised QOS metrics. The performance analysis is done with regard to the packet delivery ratio, energy consumption, sensor network life time and delay to evidence it perfect functioning.
KeywordsIOT-WSN QOS metrics Clustering Fuzzy rule based system Neural networks and Shortest route
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