ADVANCED MACHINE LEARNING ALGORITHM FOR LOAD BALANCING IN VM MIGRATION

Author Name: 1. Prof Gaurav Nayak, 2. Mr. Pushpendra Singh

Volume/Issue: 01/11

Country: India

DOI NO.: 08.2020-25662434 DOI Link: http://www.doi-ds.org/doilink/05.2021-18523936/UIJIR

Affiliation:

¹Professor Of Lakshmi Narain College of Technology & Science, Madhya Pradesh, India

  ²Student, Lakshmi Narain College of Technology & Science, Madhya Pradesh, India

ABSTRACT

Some of the disadvantages that many the use of these methods and their inability to measure parameters such as scaffolding, throughput, availability of resources etc. are inadequate heterogeneities, geography of tasks and resources and the issue of deadlocks and overload of servers. Based on this information, an algorithm has been offered for VM live migration (VM) which allows the seamless migration of VMs from one DC to another. The algorithm proposed balances the load using a technique of dynamically weighted migration. The CloudSim simulation tool with the Cloud Analyst Simulator GUI capability was used. The proposed algorithm is compared to the recently created algorithm to show how the algorithm works. The result shows a better way to achieve a load imbalance with the proposed algorithm. Finally, the results included a number of ideas that might contribute to future research

Key words: Cloud computing, Virtual machine resource, Load balancing, virtualization, Machine Learning