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Dynamic Task Migration Mechanisms in Cloud Environment: Literature Review and Future Trends

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IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development
© 2019 by IJCA Journal
ICRTSTMSD 2018 - Number 1
Year of Publication: 2019
Authors:
Ankit Tomar
J. C. Patni
Amit Dixit
Pramod Kumar

Ankit Tomar, J C Patni, Amit Dixit and Pramod Kumar. Article: Dynamic Task Migration Mechanisms in Cloud Environment: Literature Review and Future Trends. IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development ICRTSTMSD 2018(1):21-28, August 2019. Full text available. BibTeX

@article{key:article,
	author = {Ankit Tomar and J. C. Patni and Amit Dixit and Pramod Kumar},
	title = {Article: Dynamic Task Migration Mechanisms in Cloud Environment: Literature Review and Future Trends},
	journal = {IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development},
	year = {2019},
	volume = {ICRTSTMSD 2018},
	number = {1},
	pages = {21-28},
	month = {August},
	note = {Full text available}
}

Abstract

IT sector is adopting novel cloud computing to converge the business and technology platforms in terms of ease of services which allow users to access the resources in pay as go fashion anytime and anywhere. To accomplish this goal several challenges have to face in which balancing the load among the nodes is one of them. Despite the significance of load balancing algorithms there is no organized literature which could cover or analyze the dynamic migration techniques, their scope, limitations and challenges, so this article focus on those dynamic load balancing techniques in which lot of work has done to reduce the migration time of tasks form one VM to other. Task migration is an important load balancing metric in cloud computing by relocating active virtual machines (VMs) from one candidate node to another. To achieve better system performance load must be distribute evenly across the servers, for this under loading and overloading of VM should be avoid by migrating the extra tasks in shortest period. In this literature we have given the detailed overview of qualitative and quantitative analysis of existing task migration schemes, also merits, demerits and important challenges are addressed so that more resourceful and scalable migration algorithms could be develop in near future.

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