Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
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Light Weight CNN based Robust Image Watermarking Scheme for Security
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Principle of 6G Wireless Networks: Vision, Challenges and Applications
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PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
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Is Internet becoming a Major Contributor for Global warming - The Online Carbon Footprint
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Augmented Reality in Education
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A Study on Various Task-Work Allocation Algorithms in Swarm Robotics
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IoT based Biotelemetry for Smart Health Care Monitoring System
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Tungsten DiSulphide FBG Sensor for Temperature Monitoring in Float Glass Manufacturing
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GUI based Industrial Monitoring and Control System
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AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1
Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4
Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2
Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2
VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1
Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3
Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3
PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3
Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
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Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2
Volume - 1 | Issue - 2 | december 2019
Published
December, 2019
Resource management plays the vital role in the cloud computing as the requirement for the massive data processing system such as heath sectors, business solutions and the internet of things keeps on increasing in at an exponential range. Allocation of proper and perfect resources remains as the mains reasons for the successful computation of the applications. However the conventional resources management methodologies, that totally depends on the simple heuristic based methods fails to accomplish a performance that is predictable. The appropriate resource allocation is directly related to the workload demand prediction as the would help to bring down the cost, time and power and the memory usage. The proposed method in the paper leverages the machine learning approaches to manage the resource allocation in the cloud computing for the massive data processing system, the simulation of the proposed model using the network simulator -2 enables to achieve a better performance and resources utilization at a decreased cost, time, power and memory usage.
KeywordsCloud Computing Resource Allocation Work Load Prediction Massive Data Processing System Machine Learning Algorithms
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