Affiliation:
1. Department of Computer Science & Technology, Manav Rachna University, Faridabad, India
2. Department of Computer
Science & Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Sonepat, India
Abstract
Background:
Virtualization adequately maintains increasing requirements for storage,
networking, servers, and computing in exhaustive cloud data centers (CDC)s. Virtualization assists
in gaining different objectives like dedicated server sustenance, fault tolerance, comprehensive service
availability, and load balancing, by virtual machine (VM) migration. The VM migration process
continuously requires CPU cycles, communication bandwidth, memory, and processing power.
Therefore, it detrimentally prevails over the performance of dynamic applications and cannot be
completely neglected in the synchronous large-scale CDC, explicitly when service level agreement
(SLA) and analytical trade goals are to be defined.
Introduction:
Live VM migration is intermittently adopted as it grants the operational service even
when the migration is executed. Currently, power competence has been identified as the primary
design requirement for the current CDC model. It grows from a single server to numerous data centres
and clouds, which consume an extensive amount of electricity. Consequently, appropriate energy
management techniques are especially important for CDCs.
Method:
This review paper delineates the need for energy efficiency in the CDC, the systematic
mapping of VM migration methods, and research pertinent to it. After that, an analysis of VM migration
techniques, the category of VM migration, duplication, and context-based VM migration is
presented along with its relative analysis.
Results:
The various VM migration techniques were compared on the basis of various performance
measures. The techniques based on duplication and context-based VM migration methods provide
an average reduction in migration time of up to 38.47%, data transfer rate of up to 51.4%, migration
downtime of up to 36.33%, network traffic rate of up to 44% and reduced application efficiency
overhead up to 14.27%.
Conclusion:
The study aids in analyzing threats and research challenges related to VM migration
techniques which ultimately help in exploring future research directions that would help aspiring
cloud professionals.
Publisher
Bentham Science Publishers Ltd.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Load Balancing Approach Using Binary Search;Lecture Notes in Networks and Systems;2024
2. Car Parking Technique for Load Balancing in Cloud Data Centres;2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2023-12-15
3. Enhancing Virtual Machine Migration in Cloud Environments;2023 1st DMIHER International Conference on Artificial Intelligence in Education and Industry 4.0 (IDICAIEI);2023-11-27