MACHINE LEARNING APPROACH FOR LOAD BALANCING OF VM PLACEMENT CLOUD COMPUTING

Abstract

Load balance is the technique of distributing loads to a number of services in various networks. As a result, loads want to be distributed around cloud-based networks, so that each resource plays virtually the same function at different times. The crucial pre-requisite is to provide a quantity of resources to maintain queries in order to operate the program more effectively. Every cloud provider relies on day-to-day load balancing services that allow customers to increase the amount of CPUs or memory to compare their resources to help suit their needs. Its services are optional and unique to the client. We Proposed and Recommend and analyze all of the load balancing algorithms that run in the Cloud Analyst tool and suggest a new modified algorithm that will improve response time and lower costs.