LOAD BALANCING IN CLOUD USING META-HEURISTIC BEES SWARM SCHEDULING

Abstract
For virtualized file sharing, cloud storage uses scripting and load balancing in the cloud architecture. The two must be designed for optimum file sharing in the cloud computing environment. Latest advances in cloud data centre have been made in flexible traffic control for traffic balancing and service efficiency. But the delay during multidimensional resource distribution remains a problem. There is also a need for effective resource planning to guarantee cloud load optimization. In this post, we create an optimised algorithm for the preparation of resources and load balancing to provide efficient cloud services. The methodology provides a multidimensional resource planning paradigm for effective resource planning of cloud networks based on Bees Swarm Optimisation (BSO). A stable and balanced load-equilibrium makes the dynamically chosen request in a class with a multidimensional queuing load-optimization algorithm. A load balancing algorithm is then introduced to ensure resource understatement and overuse, which raises the latency period for each application form. Simulations have been undertaken for performance evaluation in the cloud data centre using Cloudsim simulators, and findings suggest that the approach suggested contributes to improved success rates, resource planning efficiency and response time.

Authors
M Ramesh
Bharathiar University, India

Keywords
Task Scheduling, Bees Swarm Optimisation, Resource Allocation, Scalable Traffic Management
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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