MULTI-CLOUD FRAMEWORK ON MACHINE LEARNING RESOURCE ALLOCATION

Abstract
In this paper, we suggest a multi-stage ML-RA system to increase the performance of existing and future cloud storage, which includes a QoS Resource Distribution that limits the volume of data to be shared in the Cloud to process and store. The proposed ML-RA method is capable of transferring all data from IoT to the cloud, which allows ML-RA to get server managers closer to the client. It is very difficult to grasp cloud computing without space sharing due to capableness and infrastructure costs. The paper has developed an appropriate ML-RA system and algorithm to check and test the efficiency of the cloud on the Cloudsim tool. This paper was planned and implemented Results shows an optimal algorithm for resource allocation is the suggested multi-stage ML-RA method which is easily scalable.

Authors
D Viknesh Kumar
Sriguru Institute of Technology, India

Keywords
Cloud Computing, Resource Allocation, Quality of Service, Energy Efficiency, Scheduling, Virtualization
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 3 )
Date of Publication :
June 2020

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