Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications
Luis Eduardo Bautista Villalpando, Alain April, Alain Abran
2014
Abstract
Cloud Computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources. Cloud Computing users prefer not to own physical infrastructure, but instead rent Cloud infrastructure, a Cloud platform or software, from a third-party provider. Sometimes, anomalies and defects affect a part of the Cloud platform, resulting in degradation of the Cloud performance. One of the challenges in identifying the source of such degradation is how to determine the type of relationship that exists between the various performance metrics which affect the quality of the Cloud and more specifically Cloud applications. This work uses the Taguchi method for the design of experiments to propose a methodology for identifying the relationships between the various configuration parameters that affect the quality of Cloud Computing performance in Hadoop environments. This paper is based on a proposed performance measurement framework for Cloud Computing systems, which integrates software quality concepts from ISO 25010 and other international standards.
References
- Bautista, L., A. Abran, et al. (2012). "Design of a Performance Measurement Framework for Cloud Computing." Journal of Software Engineering and Applications 5(2): 69-75.
- Cheikhi, L. and A. Abran (2012). "Investigation of the Relationships between the Software Quality Models of ISO 9126 Standard: An Empirical Study using the Taguchi Method." Software Quality Professional Magazine.
- Dean, J. and S. Ghemawat (2008). "MapReduce: simplified data processing on large clusters." Communications of the ACM 51(1): 107-113.
- Hadoop, A. F. (2012). "What Is Apache Hadoop?", from http://hadoop.apache.org/.
- ISO/IEC (2008). ISO/IEC 15939:2007 Systems and software engineering - Measurement process. Geneva, Switzerland, International Organization for Standardization.
- ISO/IEC (2011). ISO/IEC 25010: Systems and software engineering - Systems and software product Quality Requirements and Evaluation (SQuaRE) - System and software quality models. Geneva, Switzerland, International Organization for Standardization: 43.
- ISO/IEC (2011). ISO/IEC JTC 1 SC38:Study Group Report on Cloud Computing. Geneva, Switzerland, International Organization for Standardization.
- Jackson, K. R., L. Ramakrishnan, et al. (2010). Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud. IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom), Washington, DC, USA, IEEE Computer Society.
- Jain, R. (1991). The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. New York, NY, John Wiley & Sons - Interscience.
- Kramer, W., J. Shalf, et al. (2005). The NERSC Sustained System Performance (SSP) Metric. California, USA, Lawrence Berkeley National Laboratory.
- Lin, J. and C. Dyer (2010). Data-Intensive Text Processing with MapReduce. University of Maryland, College Park, Manuscript of a book in the Morgan & Claypool Synthesis Lectures on Human Language Technologies.
- Mei, Y., L. Liu, et al. (2010). Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud. IEEE International Conference on Cloud Computing, CLOUD 2010, Miami, FL, USA, IEEE.
- Mell, P. and T. Grance (2011). The NIST Definition of Cloud Computing. Gaithersburg, MD, USA, Information Technology Laboratory, National Institute of Standards and Technology: 2-3.
- Taguchi, G., S. Chowdhury, et al. (2005). Taguchi's Quality Engineering Handbook, John Wiley & Sons, New Jersey.
- Trivedi, K. S. (2002). Probability and Statistics with Reliability, Queuing and Computer Science Applications. New York, U.S.A., John Wiley & Sons, Inc.
Paper Citation
in Harvard Style
Villalpando L., April A. and Abran A. (2014). Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications . In Proceedings of the 4th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-019-2, pages 375-386. DOI: 10.5220/0004725403750386
in Bibtex Style
@conference{closer14,
author={Luis Eduardo Bautista Villalpando and Alain April and Alain Abran},
title={Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications},
booktitle={Proceedings of the 4th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2014},
pages={375-386},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004725403750386},
isbn={978-989-758-019-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 4th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications
SN - 978-989-758-019-2
AU - Villalpando L.
AU - April A.
AU - Abran A.
PY - 2014
SP - 375
EP - 386
DO - 10.5220/0004725403750386