research-article

Software aging in the eucalyptus cloud computing infrastructure: Characterization and rejuvenation

Authors:

F. Vieira de Souza,

Rivalino Matias Jr.,

Kishor S. TrivediAuthors Info & Claims

ACM Journal on Emerging Technologies in Computing Systems (JETC), Volume 10, Issue 1

Article No.: 11, Pages 1 - 22

https://doi.org/10.1145/2539122

Published: 13 January 2014 Publication History

Abstract

The need for high reliability, availability and performance has significantly increased in modern applications, that handle rapidly growing demands while providing uninterruptible services. Cloud computing systems fundamentally provide access to large pools of data and computational resources. Eucalyptus is a software framework largely used to implement private clouds and hybrid-style Infrastructure as a Service. It implements the Amazon Web Service (AWS) API, allowing interoperability with other AWS-based services. This article investigates the software aging effects in the Eucalyptus framework, considering workloads composed of intensive requests for remote storage attachment and virtual machine instantiations. We found problems that may be harmful to system dependability and performance, specifically regarding to RAM memory and swap space exhaustion, besides highly excessive CPU utilization by the virtual machines. We also present an approach that applies time series analysis to schedule rejuvenation, so as to reduce the downtime by predicting the proper moment to perform the rejuvenation. We experimentally evaluate our approach using an Eucalyptus test bed. The results show that our approach achieves higher availability, when compared to a threshold-triggered rejuvenation method based on continuous monitoring of resources utilization.

References

[1]

Akaike, H. 1969. Fitting autoregressive models for prediction. Ann. Institute Stat. Math. 21, 1, 243--247.

[2]

Amazon. 2011a. Amazon Elastic Block Store (EBS). Amazon.com, Inc. Available in: http://aws.amazon.com/ebs.

[3]

Amazon. 2011b. Amazon elastic compute cloud - ec2. Amazon.com, Inc.

[4]

Araujo, J., Matos Junior, R., Maciel, P., and Matias, R. 2011a. Software aging issues on the eucalyptus cloud computing infrastructure. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC'11). Anchorage.

[5]

Araujo, J., Matos Junior, R., Maciel, P., Matias, R., and Beicker, I. 2011b. Experimental evaluation of software aging effects on the eucalyptus cloud computing infrastructure. In Proceedings of the ACM/IFIP/USENIX International Middleware Conference (Middleware'11). Lisbon.

Digital Library

[6]

Araujo, J., Matos Junior, R., Maciel, P., Vieira, F., Matias, R., and Trivedi, K. S. 2011c. Software rejuvenation in eucalyptus cloud computing infrastructure: A method based on time series forecasting and multiple thresholds. In Proceedings of the 3rd International Workshop on Software Aging and Rejuvenation (WoSAR'11) in conjuction with the 22nd Annual International Symposium on Software Reliability Engineering (ISSRE'11). Hiroshima.

Digital Library

[7]

Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., and Zaharia, M. 2009. Above the clouds: A Berkeley view of cloud computing. Tech. Rep. UCB/EECS-2009-28, UC Berkeley Reliable Adaptive Distributed Systems Laboratory. Feb.

[8]

Avizienis, A., Laprie, J., Randell, B., and Landwehr, C. 2004. Basic concepts and taxonomy of dependable and secure computing. IEEE Trans. Depend. Secure Comput. 1, 11--33.

Digital Library

[9]

Bao, Y., Sun, X., and Trivedi, K. S. 2005. A workload-based analysis of software aging and rejuvenation. IEEE Trans. Reliab. 54, 541--548.

[10]

Bloomfield, P. 2000. Fourier Analysis of Time Series: An Introduction. Wiley Series in Probability and Statistics.

[11]

Blum, R. 2008. Linux Command Line and Shell Scripting Bible. Wiley.

Digital Library

[12]

Box, G. and Jenkins, G. 1970. Time Series Analysis. Holden-Day series in time series analysis. Holden-Day, San Francisco, CA.

[13]

Canonical. 2011. Manual pages about using a GNU/Linux system. Canonical Ltd. Available in: http://manpages.ubuntu.com/manpages/hardy/man5/proc.5.html.

[14]

Carrozza, G., Cotroneo, D., Natella, R., Pecchia, A., and Russo, S. 2010. Memory leak analysis of mission-critical middleware. J. Syst. Softw. 83, 1556--1567.

Digital Library

[15]

Chatfield, C. 1996. The Analysis of Time Series: An Introduction 5th Ed. Chapman & Hall/CRC, New York.

[16]

Cordeiro, T., Damalio, D., Pereira, N., Endo, P., Palhares, A., Goncalves, G., Sadok, D., Kelner, J., Melander, B., Souza, V., and Mångs, J.-E. 2010. Open source cloud computing platforms. In Proceedings of the 9th International Conference on Grid and Cloud Computing (GCC'2010) (Jiangsu). 1--5.

Digital Library

[17]

Cully, B., Lefebvre, G., Meyer, D., Feeley, M., Hutchinson, N., and Warfield, A. 2008. Remus: High availability via asynchronous virtual machine replication. In Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation (San Francisco). 161--174.

Digital Library

[18]

Eucalyptus. 2009. Eucalyptus Open-Source Cloud Computing Infrastructure - An Overview. Eucalyptus Systems, Inc., 130 Castilian Drive, Goleta, CA 93117 USA.

[19]

Eucalyptus. 2010. Cloud Computing and Open Source: IT Climatology is Born. Eucalyptus Systems, Inc., 130 Castilian Drive, Goleta, CA 93117 USA.

[20]

Eucalyptus. 2011. Eucalyptus - the open source cloud platform. Eucalyptus Systems, Inc. Available in: http://open.eucalyptus.com/.

[21]

Grottke, M., Matias, R., and Trivedi, K. 2008. The fundamentals of software aging. In Proceedings of the 1st International Workshop on Software Aging and Rejuvenation (WoSAR), in conjunction with the 19th IEEE International Symposium on Software Reliability Engineering (Seattle).

[22]

Huang, Y., Kintala, C., Kolettis, N., and Fulton, N. D. 1995. Software rejuvenation: Analysis, module and applications. In Proceedings of the 25th Symposium on Fault Tolerant Computing (FTCS-25) (Pasadena). 381--390.

Digital Library

[23]

Iosup, A., Ostermann, S., Yigitbasi, N., Prodan, R., Fahringer, T., and Epema, D. 2011. Performance analysis of cloud computing services for many-tasks scientific computing. IEEE Trans. Paral. Distrib. Syst. (TPDS), Special Issue on Many-Task Computing 22, 931--945.

Digital Library

[24]

Johnson, D., Murari, K., Raju, M., RB, S., and Girikumar, Y. 2010. Eucalyptus Beginner's Guide UEC Ed. For Ubuntu Server 10.04 - Lucid Lynx, v1.0.

[25]

Jones, M. T. 2008. Cloud computing with Linux - cloud computing platforms and applications. IBM Corporation, 12.

[26]

Kedem, B. and Fokianos, K. 2002. Regression Models for Time Series Analysis. Wiley.

[27]

Kourai, K. and Chiba, S. 2007. A fast rejuvenation technique for server consolidation with virtual machines. In Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07) (Washington). 245--255.

Digital Library

[28]

KVM. 2012. Kernel based virtual machine. Project Home Page. Available in: http://www.linux-kvm.org.

[29]

Machida, F., Kim, D. S., and Trivedi, K. 2010. Modeling and analysis of software rejuvenation in a server virtualized system. In Proceedings of the 2010 IEEE 2nd International Workshop on Software Aging and Rejuvenation (WoSAR). 1--6.

[30]

Matias, R. and Filho, P. J. F. 2010. Measuring software aging effects through OS kernel instrumentation. In Proceedings of the 2nd International Workshop on Software Aging and Rejuvenation (WoSAR), in conjunction with 21th IEEE International Symposium on Software Reliability Engineering (ISSRE'10) (San Jose).

[31]

Matias, R. and Freitas Filho, P. J. 2006. An experimental study on software aging and rejuvenation in web servers. In Proceedings of the 30th Annual International Computer Software and Applications Conference (COMPSAC'06) (Chicago).

Digital Library

[32]

Matias Jr., R., Barbetta, P. A., Trivedi, K. S., and Filho, P. J. F. 2010. Accelerated degradation tests applied to software aging experiments. IEEE Trans. Reliab. 59, 1, 102--114.

[33]

Matos Jr., R., Araujo, J., Maciel, P., Vieira, F., Matias, R., and Trivedi, K. S. 2011. Software rejuvenation in Eucalyptus cloud computing infrastructure: A hybrid method based on multiple thresholds and time series prediction. Int. Trans. Syst. Sci. Appl. 7, 295--303.

[34]

McKinley, P. K., Samimi, F. A., Shapiro, J. K., and Tang, C. 2006. Service clouds: A distributed infrastructure for composing autonomic communication services. In Proceedings of the 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC'06) (Indianapolis, IN). 341--348.

Digital Library

[35]

Mihailescu, M., Rodriguez, A., and Amza, C. 2011. Enhancing application robustness in infrastructure-as-a-service clouds. In Proceedings of the 1st International Workshop on Dependability of Clouds, Data Centers and Virtual Computing Environments (DCDV 2011) in conjunction with the 41st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'11) (Hong Kong).

Digital Library

[36]

Montgomery, D. C., Jennings, C. L., and Kulahci, M. 2008. Introduction to Time Series Analysis and Forecasting. Wiley series in probability and statistics.

[37]

Musa, J. D. 1998. Software Reliability Engineering: More Reliable Software, Faster Development and Testing 2 Ed. McGraw-Hill, New York, NY.

Digital Library

[38]

NIST. 2011. NIST. National Institute of Standards and Technology, Information Technology Laboratory, U.S. Department of Commerce. Available in: http://csrc.nist.gov.

[39]

Paing, A. M. M. and Thein, N. L. 2012. Stochastic reward nets model for time based software rejuvenation in virtualized environment. Int. J. Comput. Sci. Telecommuni. 3, 1, 1--10.

[40]

Peng, J., Zhang, X., Lei, Z., Zhang, B., Zhang, W., and Li, Q. 2009. Comparison of several cloud computing platforms. In Proceedings of the 2nd International Symposium on Information Science and Engineering (ISISE) (Shanghai). IEEE Press, 23--27.

Digital Library

[41]

Rezaei, A. and Sharifi, M. 2010. Rejuvenating high available virtualized systems. In Proceedings of the International Conference on Availability, Reliability, and Security, 2010 (ARES'10). 289--294.

[42]

Schwarz, G. 1978. Estimating the dimension of a model. Ann. Stati.

[43]

Sousa, E., Maciel, P. R. M., Arajo, C., Alves, G., and Chicout, F. 2009. Performance modeling for evaluation and planning of electronic funds transfer systems. In Proceedings of ISCC'09. 73--76.

[44]

Sun, D., Chang, G., Guo, Q., Wang, C., and Wang, X. 2010. A dependability model to enhance security of cloud environment using system-level virtualization techniques. In Proceedings of the 1st International Conference on Pervasive Computing, Signal Processing and Applications. 6.

Digital Library

[45]

Sun Microsystems. 2009. Introduction to Cloud Computing Architecture 1 Ed. Sun Microsystems, Inc.

[46]

Trivedi, K. S., Kim, D. S., Roy, A., and Medhi, D. 2009. Dependability and security models. In Proceedings of the 7th International Workshop on the Design of Reliable Communication Networks (DRCN'09).

[47]

Vaidyanathan, K. and Trivedi, K. S. 2005. A comprehensive model for software rejuvenation. IEEE Trans. Depend. Secure Comput. 2, 124--137.

Digital Library

[48]

Witkon, E. 2007. Using Load Testing to meet Your SLA. RadView Software. RadView Executive White Paper.

[49]

Xie, M., Dai, Y.-S., and Poh, K.-L. 2004. Computing System Reliability: Models and Analysis. Kluwer Academic Publishers.

Digital Library

Cited By

Meng HZhang J(2024)A novel multi-step-ahead approach for cloud server aging prediction based on hybrid deep learning modelEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108588133(108588)Online publication date: Jul-2024
https://doi.org/10.1016/j.engappai.2024.108588
Andrade EPietrantuono RMachida FCotroneo D(2023)A Comparative Analysis of Software Aging in Image Classifiers on Cloud and EdgeIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.313920120:1(563-573)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TDSC.2021.3139201
Battisti FSilva APereira LCarvalho TAraujo JChoi ENguyen TMin D(2022)hLSTM-Aging: A Hybrid LSTM Model for Software Aging ForecastApplied Sciences10.3390/app1213641212:13(6412)Online publication date: 24-Jun-2022
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Index Terms

Software aging in the eucalyptus cloud computing infrastructure: Characterization and rejuvenation
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
2. General and reference
  1. Cross-computing tools and techniques

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Information

Published In

cover image ACM Journal on Emerging Technologies in Computing Systems

ACM Journal on Emerging Technologies in Computing Systems Volume 10, Issue 1

Special Issue on Reliability and Device Degradation in Emerging Technologies and Special Issue on WoSAR 2011

January 2014

210 pages

ISSN:1550-4832

EISSN:1550-4840

DOI:10.1145/2543749

Editors:
Rahul Rao
Technology and Hardware Lab, IBM, India
,
Fadi Gebara
Austin Research Lab, IBM USA
,
Alberto Avritzer
Siemens Corporation, Research and Technology, USA
,
Tadashi Dohi
Hiroshima University, Japan

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Copyright © 2014 ACM.

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 13 January 2014

Accepted: 01 November 2012

Revised: 01 September 2012

Received: 01 April 2012

Published in JETC Volume 10, Issue 1

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Cited By

Meng HZhang J(2024)A novel multi-step-ahead approach for cloud server aging prediction based on hybrid deep learning modelEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108588133(108588)Online publication date: Jul-2024
https://doi.org/10.1016/j.engappai.2024.108588
Andrade EPietrantuono RMachida FCotroneo D(2023)A Comparative Analysis of Software Aging in Image Classifiers on Cloud and EdgeIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.313920120:1(563-573)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TDSC.2021.3139201
Battisti FSilva APereira LCarvalho TAraujo JChoi ENguyen TMin D(2022)hLSTM-Aging: A Hybrid LSTM Model for Software Aging ForecastApplied Sciences10.3390/app1213641212:13(6412)Online publication date: 24-Jun-2022
https://doi.org/10.3390/app12136412
Carnevali LPaolieri MReali RScommegna LVicario E(2022)A Markov Regenerative Model of Software Rejuvenation Beyond the Enabling Restriction2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW55968.2022.00060(138-145)Online publication date: Oct-2022
https://doi.org/10.1109/ISSREW55968.2022.00060
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Vizarreta PSieber CBlenk AVan Bemten ARamachandra VKellerer WMas-Machuca CTrivedi K(2021)ARES: A Framework for Management of Aging and Rejuvenation in Softwarized NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2020.303058918:2(1389-1400)Online publication date: Jun-2021
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da Costa Jde S. Matos Rde Araujo JMaciel P(2021)Systematic Mapping of Literature on Software Aging and Rejuvenation Research Trends2021 Annual Reliability and Maintainability Symposium (RAMS)10.1109/RAMS48097.2021.9605775(1-6)Online publication date: 24-May-2021
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Andrade EMachida FPietrantuono RCotroneo D(2021)Memory Degradation Analysis in Private and Public Cloud Environments2021 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW53611.2021.00041(33-39)Online publication date: Oct-2021
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Wang SLu MKong SAi J(2020)A Dynamic Anomaly Detection Approach Based on Permutation Entropy for Predicting Aging-Related FailuresEntropy10.3390/e2211122522:11(1225)Online publication date: 27-Oct-2020
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