A ProperFit Virtual Machine Migration Approach for the Load Balancing in Cloud

Authors

  • Tiwari D Dept. of Computer Science & Engineering Bansal Institute of Science and Technology Bhopal, India
  • Singh S Dept. of Computer Science & Engineering Bansal Institute of Science and Technology Bhopal, India
  • Sharma S Dept. of SOIT Rajiv Gandhi Proudyogiki Vishwavidyalaya Bhopal, India

DOI:

https://doi.org/10.26438/ijcse/v6i12.433436

Keywords:

Migration, energy efficient, virtualization, VM selection, VM placement, SLA violation

Abstract

With the invention of the cloud computing, the utilization of the physical resources has improved drastically. The main technology that enable the cloud computing is virtualization which allows to create several virtual machine (VM)onto the single physical machine (PM). It increased the utilization of the physical resources because single hardware resources are shared by the several users. Although virtualization technique optimize the server utilization but add new issue named load balancing that need to addressed for the effective utilization of the physical resource and maintain the quality of services (QoS). To deal with the load balancing VM migration approach is used which permit to travel the VM from physical machine (host) to another. Three stages are engaged with the relocation procedure i.e., source PM choice, VM selection and the last step is target PM selection. Plenty of work on the load balancing in cloud are presented in the last few decades and mostly they are differ in the VM selection and VM placement polices. After the study of previous work on the VM migration it can be says that choosing an appropriate VM is a non-trival task and the performance of the load balancing approach is mainly depends on the appropriate VM selection polices. In this paper we select the three different types of virtual machine for the migration and then placed it to the physical machine where the load on the physical machine is between 20 to 50. CloudSim simulator is used to evaluate the performance of the physical.

References

[1] R. Buyya et al., “Market Oriented cloud computing: vision, hype and reality for delivering it services as computing utilities,” CoRR, 2008.

[2] P. Mell et al, “NIST definition of cloud computing,” vol. 15, October 2009.

[3] Introduction to Cloud Computing, available at http://www.webopedia.com/TERM/C/cloud_computing.html

[4] Rajeev Kumar Gupta and R.K. Pateriya,” Balance Resource Utilization (BRU) Approach for the Dynamic Load Balancing in Cloud Environment by using AR Prediction Model ”, Journal of Organizational and End User Computing (JOEUC), Volume 29, Issue 4, Article 2, 2017.

[5] A. Rabiatul et al., "Virtual Machine Migration Implementation in Load Balancing for Cloud Computing", six IEEE international conference, 2014.

[6] A Jain et al., “A Threshold Band Based Model For Automatic Load Balancing in Cloud Environment”, in proc. of IEEE International Conference on Cloud Computing in Emerging Markets, pp 1-7, 2013.

[7] A. Awad et al., " Enhanced Particle Swarm Optimization For Task Scheduling In Cloud Computing Environments", International Conference on Communication, Management and Information Technology (ICCMIT), ScienceDirect, pp. 920 – 929, 2015.

[8] G.Shobana et al., "Nature Inspired Preemptive Task Scheduling for Load Balancing in Cloud Datacenter", International Conference on Information Communication and Embedded Systems (ICICES), pp. 1-6, 2014.

[9] R. Addawiyah et al., "Virtual Machine Migration Implementation in Load Balancing for Cloud Computing", six IEEE international conference, 2014.

[10] Lei Xu et al., "An Integrated Dynamic Resource Scheduling Framework in On-Demand Clouds", journal of Information Science and Engineering, pp. 1-8, 2015.

[11] Y. Fang, F. Wang, and J. Ge, “A Task Scheduling Algorithm Based on Load Balancing in Cloud Computing”, Web Information Systems and Mining, Lecture Notes in Computer Science, Vol.63, pages 271-277, 2010.

[12] R. Calheiros, R Ranjan, César A. F. De Rose, R. Buyya, “ CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services” , 2011.

[13] B. Wickremasingh et al.. "A CloudSim-based Visual Modeller for Analyzing Cloud Computing Environments and Applications”, in: Proceedings 24th International Conference on Advanced Information Networking and Applications (AI NA), 2010.

Downloads

Published

2018-12-31
CITATION
DOI: 10.26438/ijcse/v6i12.433436
Published: 2018-12-31

How to Cite

[1]
D. Tiwari, S. Singh, and S. Sharma, “A ProperFit Virtual Machine Migration Approach for the Load Balancing in Cloud”, Int. J. Comp. Sci. Eng., vol. 6, no. 12, pp. 433–436, Dec. 2018.

Issue

Vol. 6 No. 12 (2018): IJCSE December Editor

Section

Survey Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.