A heuristic based algorithm for distance-aware virtual machine allocation in cloud
Article No.: 157, Pages 1 - 5
Abstract
MapReduce-as-a-Service cloud is of great importance because of the data growth and increase in opportunities in big data analytics. MapReduce platforms provided through cloud help the end user by providing ready to use MapReduce clusters. Since the cloud environment is virtualized, allocating Virtual Machines (VMs) efficiently has high relevance. If the VMs allocated for a MapReduce cluster are hosted in distant Physical Machines (PMs), the interaction between VMs causes delays depending upon the distance between the PMs hosting them. In this paper, we propose a heuristic algorithm for VM allocation for providing MapReduce as a cloud service. This algorithm allocates VMs in same or nearby PMs and hence reduces data transfer delay between VMs. Simulation results demonstrate the improvement on execution time of the VM allocation algorithm without compromising the performance of applications running on the allocated VMs.
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Information
Published In
March 2017
1349 pages
ISBN:9781450347747
DOI:10.1145/3018896
- General Chair:
- Hani Hamdan,
- Program Chairs:
- Homero Toral-Cruz,
- Sedat Akleylek,
- Hamid Mcheick,
- Publications Chair:
- Djallel Eddine Boubiche
Copyright © 2017 ACM.
© 2017 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 March 2017
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ICC '17
ICC '17: Second International Conference on Internet of Things, Data and Cloud Computing
March 22 - 23, 2017
Cambridge, United Kingdom
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ICC '17 Paper Acceptance Rate 213 of 590 submissions, 36%;
Overall Acceptance Rate 213 of 590 submissions, 36%
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