Research Article | OPEN ACCESS
A Qualitative and Quantitative Analysis of Multi-core CPU Power and Performance Impact on Server Virtualization for Enterprise Cloud Data Centers
1S. Suresh and 2S. Sakthivel
1Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Hosur-635109
2Department of Computer Science and Engineering, Sona College of Technology, TPTC Main Road, Salem-636005, Tamil Nadu, India
Research Journal of Applied Sciences, Engineering and Technology 2015 6:471-477
Received: October 15, ‎2014 | Accepted: November ‎3, ‎2014 | Published: February 25, 2015
Abstract
Cloud is an on demand service provisioning techniques uses virtualization as the underlying technology for managing and improving the utilization of data and computing center resources by server consolidation. Even though virtualization is a software technology, it has the effect of making hardware more important for high consolidation ratio. Performance and energy efficiency is one of the most important issues for large scale server systems in current and future cloud data centers. As improved performance is pushing the migration to multi core processors, this study does the analytic and simulation study of, multi core impact on server virtualization for new levels of performance and energy efficiency in cloud data centers. In this regard, the study develops the above described system model of virtualized server cluster and validate it for CPU core impact for performance and power consumption in terms of mean response time (mean delay) vs. offered cloud load. Analytic and simulation results show that multi core virtualized model yields the best results (smallest mean delays), over the single fat CPU processor (faster clock speed) for the diverse cloud workloads. For the given application, multi cores, by sharing the processing load improves overall system performance for all varying workload conditions; whereas, the fat single CPU model is only best suited for lighter loads. In addition, multi core processors don’t consume more power or generate more heat vs. a single-core processor, which gives users more processing power without the drawbacks typically associated with such increases. Therefore, cloud data centers today rely almost exclusively on multi core systems.
Keywords:
Analytical model , cloud computing, cloud workloads , server consolidation , simulation model,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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