An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 2 | Issue - 1 | march 2020
Published
27 March, 2020
A WANET is a specific type of Adhoc network with a community of specialized, self-organizing mobile devices. Because of the complex existence of mobile devices and wireless networking, the adhoc network communicating in wireless manner faces many problems related to the topological organizations , battery capacity limitations that results in energy restrictions, transmission of information, etc. The significant attributes of an adhoc network communicating in wireless manner are the quality of service and the percentage of energy used. Nowadays as the bio-inspired computing plays a major role in the research field. Specifically bio-inspired algorithms motivated by nature's actions are used immensely to accomplish optimization in issues faced in communication. Massive works have been reported in the recent years to enhance the quality of service utilizing the Bio-inspired computing due to its intelligent and adaptive nature. The paper proposes the intelligent and an adaptive routing employing the bio inspired genetic bee colony algorithm and the ant colony optimization to have optimized energy utilization maximizing the longevity of the network. The proposed method is evaluated suing the network simulator-2 on the basis of the energy utilization, longevity and the service quality (Throughput) of the network, the results observed for the method put forth were better compared to the existing methods.
KeywordsAdhoc Network Wireless Adhoc Network (WANET) Bio Inspired Computing Genetic Bee Colony Algorithm Adaptive and Intelligent Routing
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