Abstract
Cloud Computing is a fastest growing era of computer science. It provides computing services through the internet. With the huge demand of the cloud resources over past few decades, load balancing is the major issue for the cloud provider. To achieve the proper load balancing virtual machine (VM) migration is used. Over past few decades, several VM migration approach have been proposed, but main challenging issue in these approach is to diminish the downtime (time for which VM is unavailable) and total migration time (time required to finish the migration process). To handle mentioned issues, this paper introduced Multi phase pre-copy based live migration approach. It works in multi phases such as: In first phase, it transferring all memory pages. In second phase, it maintain the history of each pages and according to this it takes a decision whether to send this page or not. After the second phase AR forecasting approach is use to predict the page behavior in the next interval which helps to determine either to send this page or not. CloudSim simulation tools is utilized to estimate the overall performance of the process. Experiment result says that proposed approach minimize Total migration Time (TMT), Downtime (DT).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
SangeetaSharma, Meenu Chawla, “A technical review for efficient virtual machine migration”, in IEEE International conference on cloud & ubiquitous computing & emerging technologies (CUBE), pp. 20–25, 2013
Kaur, Pankajdeep, Rani, Anita: Virtual Machine Migration in Cloud Computing. International Journal of Grid Distribution Computing 8(5), 337–342 (2015)
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
W. Lio, Tao Fan et.al, “ Live migration of virtual machine based on recovering system and CPU scheduling”, In Proc. ITAC, China, pp. 1088-1096, 2011
C. Clark, K. Fraser et al., “Live Migration of Virtual Machines”, Proc. The 2nd conference on Symposium on Networked Systems Design & Implementation, pp. 273-286, 2005
F. Ma, F. Liu, and Z. Liu, “Live Virtual Machine Migration Based on Improved Pre-copy Approach“, In Proc. IEEE Int’l Conf. on Software Engineering and Service Sciences (ICSESS). IEEE, Vol.7 No.10, pp.230-233, 2010
W. Cui and M. Song, “Live memory migration with matrix bitmap algorithm”, in Proceedings of the IEEE 2nd Symposium on Web Society (SWS ’10), pp. 277–281, August 2010
S. Sharma, M. Chawla, “Three phase optimization method for precopy based VM live migration”, SpringerPlus journal, 2016
B. Hu, Z. Lei, Y. Lei, D. Xu, and J. Li, “A Time-Series Based Precopy Approach for Live Migration of Virtual Machines”, IEEE 17th International Conference on Parallel and Distributed Systems, pp. 947-952, 2011
H.Liu, H. Jin, X. Liao, L. Hu, and C. Yu, “Live migration of virtual machine based on full system trace and replay,” in Proceedings of the 18th International Symposium on High Performance Distributed computing (HPDC’09), pp.101-110, 2009
R. Calheiros et al. “ CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services”, 2011
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Shukla, R., Gupta, R.K., Kashyap, R. (2019). A Multiphase Pre-copy Strategy for the Virtual Machine Migration in Cloud. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 104. Springer, Singapore. https://doi.org/10.1007/978-981-13-1921-1_43
Download citation
DOI: https://doi.org/10.1007/978-981-13-1921-1_43
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1920-4
Online ISBN: 978-981-13-1921-1
eBook Packages: EngineeringEngineering (R0)