ENERGY-EFFICIENT SCHEDULING IN CLOUD COMPUTING ENVIRONMENT USING META-HEURISTIC OPTIMISATION

ICTACT Journal on Data Science and Machine Learning ( Volume: 2 , Issue: 2 )

Abstract

The cloud computing utilization has increased markedly, leading to traffic obstruction on web servers. The high number of customers has also created a disproportionate distribution and allocation of resources in the demand for resources. The proposed work addresses the cost-effective approach to load balancing and resource planning. Implementing various algorithms to effectively allocate resources and balance the workload in the cloud also causes a high energy consumption. To make more efficient use of algorithms, we use the cloud Analyst simulator to monitor their results. Finally, our work is based on the algorithm for Cuckoo Search Algorithm (CSA) which decreases energy consumption and time of performance as compared to other algorithms.

Authors

B Anand
Dr.SNS Rajalakshmi College Of Arts and Science, India

Keywords

Energy Efficiency, Cloud Scheduling, Cuckoo Search Optimization

Published By
ICTACT
Published In
ICTACT Journal on Data Science and Machine Learning
( Volume: 2 , Issue: 2 )
Date of Publication
March 2021
Pages
180-183
DOI

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