Top

Software Quality Journal

Published in:

07-06-2019

A survey on software aging and rejuvenation in the cloud

Authors: Roberto Pietrantuono, Stefano Russo

Published in: Software Quality Journal | Issue 1/2020

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The adoption of cloud computing for providing resource and delivering services is an irreversible trend. For most IT companies, the quality of provided services is strongly dependent on reliability and performance of the underlying cloud technologies. A widely studied problem that can greatly affect the user experience is runtime software aging, whose main countermeasure is a proactive maintenance action known as rejuvenation. This article reviews the effort conducted so far by the software aging and rejuvenation (SAR) community in the cloud domain. A set of 105 papers has been examined from three source digital libraries in order to have a clear view of the state of the art. The paper characterizes the cloud-related SAR literature according to four dimensions: the publication trends, the aging analysis methods and metrics, the rejuvenation solutions, the validation approach. Results witness an increasing interest in this area (with 58% of the studies published in the last 5 years), an equivalent role of measurement-based and model-based solutions for aging analysis (42 and 40 studies, respectively) and a prevalent interest for rejuvenation (76/105 of the studies deals with rejuvenation).

previous article Guest editorial: special issue on modeling and mitigation techniques for software aging

next article Cross-project bug type prediction based on transfer learning

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

The full list of venues is available at https://github.com/rpietrantuono/SQJ2018

The count of citations is taken from the three digital libraries we used, Sciverse Scopus, IEEEXplore, and ACM DL

The number of papers is 90 because 2 papers adopt both a model-based and a measurement-based approach.

The counting excludes the 8 hybrid studies, discussed later. Also, the sum is 46 instead of 40 because 6 studies adopt 2 formalisms each.

Alonso, J., Matias, R., Vicente, E., Maria, A., Trivedi, K. (2013). A comparative experimental study of software rejuvenation overhead. Performance Evaluation, 70(3), 231–250.CrossRef

Araujo, J., Matos, R., Maciel, P., Vieira, F., Matias, R., Trivedi, K. (2011). Software rejuvenation in Eucalyptus cloud computing infrastructure: a method based on time series forecasting and multiple thresholds. In Third international workshop on software aging and rejuvenation (WoSAR) (pp. 38–43). IEEE.

Araujo, J., Matos, R., Alves, V., Maciel, P., Vieira de Souza, F., Matias, R. Jr., Trivedi, K.S. (2014). Software aging in the Eucalyptus cloud computing infrastructure: characterization and rejuvenation. ACM Journal on Emerging Technologies in Computing Systems, 10(1), 11:1–11:22.CrossRef

Avresky, D.R., Sanzo, P.D., Pellegrini, A., Ciciani, B., Forte, L. (2015). Proactive scalability and management of resources in hybrid clouds via machine learning. In 14th International Symposium on Network Computing and Applications (NCA) (pp. 114–119). IEEE.

Bartoletti, D. (2019). Predictions 2019: cloud computing comes of age as the foundation for enterprise digital transformation. [Online]. Available: https://go.forrester.com/blogs/predictions-2019-cloud-computing/.

Bovenzi, A., Cotroneo, D., Pietrantuono, R., Russo, S. (2011). Workload characterization for software aging analysis. In 22nd International Symposium on Software Reliability Engineering (ISSRE) (pp. 240–249). IEEE.

Bovenzi, A., Cotroneo, D., Pietrantuono, R., Russo, S. (2012). On the aging effects due to concurrency bugs: a case study on MySQL. In 2012 IEEE 23rd International Symposium on Software Reliability Engineering (pp. 211–220).

Bruneo, D., Distefano, S., Longo, F., Puliafito, A., Scarpa, M. (2013). Workload-based software rejuvenation in cloud systems. IEEE Transactions on Computers, 62(6), 1072–1085.MathSciNetCrossRef

Cavezza, D.G., Pietrantuono, R., Alonso, J., Russo, S., Trivedi, K.S. (2014). Reproducibility of environment-dependent software failures: an experience report. In 2014 IEEE 25th International Symposium on Software Reliability Engineering (pp. 267–276).

Chang, X., Zhang, Z., Li, X., Trivedi, K.S. (2016). Model-based survivability analysis of a virtualized system. In IEEE 41st Conference on Local Computer Networks (LCN) (pp. 611–614).

Chen, Z., Chang, X., Han, Z., Li, L. (2018). Survivability modeling and analysis of cloud service in distributed data centers. The Computer Journal, 61(9), 1296–1305.CrossRef

Columbus, L. (2018). Forrester’s 10 cloud computing predictions for 2018. [Online]. Available: https://www.forbes.com/sites/louiscolumbus/2017/11/07/forresters-10-cloud-computing-predictions-for-2018/#58f8da6d4ae1.

Cotroneo, D., Natella, R., Pietrantuono, R. (2012). Predicting aging-related bugs using software complexity metrics. Performance Evaluation, 70(3), 163–178.CrossRef

Cotroneo, D., Orlando, S., Pietrantuono, R., Russo, S. (2013). A measurement-based ageing analysis of the JVM. Software Testing, Verification and Reliability, 23(3), 199–239.CrossRef

Cotroneo, D., Natella, R., Pietrantuono, R., Russo, S. (2014). A survey of software aging and rejuvenation studies. ACM Journal on Emerging Technologies in Computing Systems, 10(1), 8:1–8:34.CrossRef

Cotroneo, D., Fucci, F., Iannillo, A.K., Natella, R., Pietrantuono, R. (2016). Software aging analysis of the Android mobile OS. In 2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE) (pp. 478–489).

Dabrowsk, C., & Mills, K. (2011). VM leakage and orphan control in open-source clouds. In IEEE Third International Conference on Cloud Computing Technology and Science (CloudCom) (pp. 554–559). IEEE.

DeCelles, S., Huang, T., Stamm, M.C., Kandasamy, N. (2016). Detecting incipient faults in software systems: a compressed sampling-based approach. In 9th IEEE International Conference on Cloud Computing (CLOUD) (pp. 303–310). IEEE.

Escheikh, M., Tayachi, Z., Barkaoui, K. (2016). Workload-dependent software aging impact on performance and energy consumption in server virtualized systems. In 27th International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 111–118). IEEE.

Escheikh, M., Barkaoui, K., Jouini, H. (2017). Versatile workload-aware power management performability analysis of server virtualized systems. Journal of Systems and Software, 125, 365–379.CrossRef

Ficco, M., Pietrantuono, R., Russo, S. (2018). Aging-related performance anomalies in the Apache storm stream processing system. Future Generation Computer Systems, 86, 975–994.CrossRef

Grottke, M., Matias, R., Trivedi, K. (2008). The fundamentals of software aging. In IEEE International Conference on Software Reliability Engineering Workshops.

Han, L., & guo Xu, J. (2013). Availability models for virtualized systems with rejuvenation. Journal of Computational Information Systems, 9(20), 8389–8396.

Huang, T., Kandasamy, N., Sethu, H., Stamm, M. (2016). An efficient strategy for online performance monitoring of datacenters via adaptive sampling. IEEE Transactions on Cloud Computing (Early Access).

Kadirvel, S., & Fortes, J.A.B. (2010). Self-caring IT systems: a proof-of-concept implementation in virtualized environments. In IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom) (pp. 433–440). IEEE.

Kitchenham, B., & Brereton, P. (2013). A systematic review of systematic review process research in software engineering. Information and Software Technology, 55(12), 2049–2075.CrossRef

Kourai, K. (2007). A fast rejuvenation technique for server consolidation with virtual machines. In 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) (pp. 245–255). IEEE.

Kourai, K. (2010). CacheMind: fast performance recovery using a virtual machine monitor. In 2010 International Conference on Dependable Systems and Networks Workshops (DSN-W) (pp. 86–92). IEEE.

Kourai, K., & Chiba, S. (2011). Fast software rejuvenation of virtual machine monitors. IEEE Transactions on Dependable and Secure Computing, 8(6), 839–851.CrossRef

Kourai, K., & Ooba, H. (2015). Zero-copy migration for lightweight software rejuvenation of virtualized systems. In Proceedings of the 6th Asia-Pacific Workshop on Systems (APSys) (pp. 7:1–7:8). ACM.

Le, M., & Tamir, Y. (2012). Applying microreboot to system software. In Sixth International Conference on Software Security and Reliability (SERE) (pp. 11–20). IEEE.

Liu, F., Cao, J., Guo, J., Zhang, B. (2013). Research the measurement method of software aging in cloud. Applied Mechanics and Materials, 392, 779–782.CrossRef

Liu, Y., Liu, W., Song, J., He, H. (2015). An empirical study on implementing highly reliable stream computing systems with private cloud. Ad Hoc Networks, 35(C), 37–50.CrossRef

Machida, F. (2013). Modeling and analysis of software rejuvenation in a server virtualized system with live VM migration. Performance Evaluation, 70(3), 212–230.CrossRef

Machida, F. (2014). Job completion time on a virtualized server with software rejuvenation. ACM Journal on Emerging Technologies in Computing Systems, 10(1), 10:1–10:26.MathSciNetCrossRef

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

Machida, F., Nicola, V.F., Trivedi, K.S. (2011). Job completion time on a virtualized server subject to software aging and rejuvenation. In Third international Workshop on Software Aging and Rejuvenation (WoSAR) (pp. 44–49). IEEE.

Machida, F., Xiang, J., Tadano, K., Maeno, Y. (2012a). Combined server rejuvenation in a virtualized data center. In 9th International Conference on Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC) (pp. 486–493). IEEE.

Machida, F., Xiang, J., Tadano, K., Maeno, Y. (2012b). Software life-extension: a new countermeasure to software aging. In 23rd International Symposium on Software Reliability Engineering (ISSRE) (pp. 131–140). IEEE.

Melo, M., Araujo, J., Matos, R., Menezes, J., Maciel, P. (2013a). Comparative analysis of migration-based rejuvenation schedules on cloud availability. In IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 4110–4115). IEEE.

Melo, M., Maciel, P., Araujo, J., Matos, R., Araujo, C. (2013b). Availability study on cloud computing environments: live migration as a rejuvenation mechanism. In 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE.

Mohan, B.R., & Reddy, G.R.M. (2015). The effect of software aging on power usage. In 9th International Conference on Intelligent Systems and Control (ISCO). IEEE.

Myint, M., & Thein, T. (2010). Availability improvement in virtualized multiple servers with software rejuvenation and virtualization. In Fourth International Conference on Secure Software Integration and Reliability Improvement (SSIRI) (pp. 156–162). IEEE.

Nguyen, T.A., Kim, D.S., Park, J.S. (2014). A comprehensive availability modeling and analysis of a virtualized servers system using stochastic reward nets. The Scientific World Journal.

Okamura, H., Yamamoto, K., Dohi, T. (2014). Transient analysis of software rejuvenation policies in virtualized system: phase-type expansion approach. Quality Technology & Quantitative Management, 11(3), 335–351.CrossRef

Petersen, K., Vakkalanka, S., Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering: an update. Information and Software Technology, 64, 1–18.CrossRef

Pietrantuono, R., & Russo, S. (2018). Software aging and rejuvenation in the cloud: a literature review. In 29th International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 257–263). IEEE.

Rahme, J., & Xu, H. (2015). A software reliability model for cloud-based software rejuvenation using dynamic fault trees. International Journal of Software Engineering and Knowledge Engineering, 25(09n10), 1491–1513.CrossRef

Rezaei, A., & Sharifi, M. (2010). Rejuvenating high available virtualized systems. In 5th International Conference on Availability, Reliability, and Security (ARES) (pp. 289–294). IEEE.

Silva, L., Alonso, J., Torres, J. (2009). Using virtualization to improve software rejuvenation. IEEE Transactions on Computers, 58(11), 1525–1538.MathSciNetCrossRef

Simeonov, D., & Avresky, D.R. (2010). Proactive software rejuvenation based on machine learning techniques. In Avresky, DR, Diaz, M, Bode, A, Ciciani, B, Dekel, E (Eds.) Cloud computing. CloudComp 2009, ser. Lecture notes of the institute for computer sciences, social-informatics and telecommunications engineering, (Vol. 34 pp. 186–200): Springer.

Sudhakar, C., Shah, I., Ramesh, T. (2014). Software rejuvenation in cloud systems using neural networks. In International Conference on Parallel, Distributed and Grid Computing (PDGC) (pp. 230–233). IEEE.

Sukhwani, H., Matias, R., Trivedi, K.S., Rindos, A. (2017). Monitoring and mitigating software aging on IBM cloud controller system. In 28th International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 266–272). IEEE.

Tan, Y., Luo, D., Wang, J. (2010). CC-VIT: virtualization intrusion tolerance based on cloud computing. In 2nd International Conference on Information Engineering and Computer Science (ICIECS). IEEE.

Thein, T., & Park, J.S. (2009). Availability analysis of application servers using software rejuvenation and virtualization. Journal of Computer Science and Technology, 24(2), 339–346.CrossRef

Thein, T., Chi, S., Park, J.S. (2008). Availability modeling and analysis on virtualized clustering with rejuvenation. International Journal of Computer Science and Network Security, 8(9), 72–80.

Torquato, M., Maciel, P., Araujo, J., Umesh, I.M. (2017). An approach to investigate aging symptoms and rejuvenation effectiveness on software systems. In 12th Iberian Conference on Information Systems and Technologies (CISTI). IEEE.

Torquato, M., Umesh, I.M., Maciel, P. (2018). Models for availability and power consumption evaluation of a private cloud with VMM rejuvenation enabled by VM live migration. The Journal of Supercomputing, 74(9), 4817–4841.CrossRef

Umesh, I.M., & Srinivasan, G.N. (2016). Optimum software aging prediction and rejuvenation model for virtualized environment. Indonesian Journal of Electrical Engineering and Computer Science, 3(3), 572–578.CrossRef

Umesh, I.M., & Srinivasan, G.N. (2017). Dynamic software aging detection-based fault tolerant software rejuvenation model for virtualized environment, ser. Advances in intelligent systems and computing (Vol. 469, pp. 779–787). Singapore: Springer.

Villalobos, J.J., Rodero, I., Parashar, M. (2014). Energy-aware autonomic framework for cloud protection and self-healing. In International Conference on Cloud and Autonomic Computing (ICCAC) (pp. 3–4). IEEE.

Wohlin, C., Runeson, P., da Mota Silveira Neto, P.A., Engstrom, E., do Carmo Machado, I., de Almeida, E.S. (2013). On the reliability of mapping studies in software engineering. Journal of Systems and Software, 86(10), 2594–2610.CrossRef

Wu, H., & Wolter, K. (2015). Software aging in mobile devices: partial computation offloading as a solution. In 26th International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 125–131). IEEE.

Xia, Y., Han, Y., Zhou, M., Li, J. (2014). A stochastic model for performance and energy consumption analysis of rejuvenation and migration-enabled cloud. In Proc. of the 2014 International Conference on Advanced Mechatronic Systems (pp. 139–144). IEEE.

Xu, J., Li, X., Zhong, Y., Zhang, H. (2014a). Availability modeling and analysis of a single-server virtualized system with rejuvenation. Journal of Software, 9 (1), 129–139.CrossRef

Xu, J., wen Wu, W., yi Ma, C. (2014b). SOM-based aging detection for virtual machine monitor. In IEEE Workshop on Electronics, Computer and Applications (pp. 782–785). IEEE.

Zhao, J., Wang, Y.-B., Ning, G.-R., Wang, C.-H., Trivedi, K.S., Cai, K. -Y., Zhang, Z.-Y. (2014). Software maintenance optimization based on Stackelberg game methods. In IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (pp. 426–430). IEEE.

Title: A survey on software aging and rejuvenation in the cloud
Authors: Roberto Pietrantuono
Stefano Russo
Publication date: 07-06-2019
Publisher: Springer US
Published in: Software Quality Journal / Issue 1/2020
Print ISSN: 0963-9314
Electronic ISSN: 1573-1367
DOI: https://doi.org/10.1007/s11219-019-09448-3

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 1/2020

Cross-project bug type prediction based on transfer learning

Availability and reliability modeling of VM migration as rejuvenation on a system under varying workload

Invalid bug reports complicate the software aging situation

Virtualization of stateful services via machine learning

On the performance of software rejuvenation models with multiple degradation levels

Guest editorial: special issue on modeling and mitigation techniques for software aging

Premium Partner