research-article

A survey of software aging and rejuvenation studies

Authors:

Domenico Cotroneo,

Roberto Natella,

Roberto Pietrantuono,

Stefano RussoAuthors Info & Claims

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

Article No.: 8, Pages 1 - 34

https://doi.org/10.1145/2539117

Published: 13 January 2014 Publication History

Abstract

Software aging is a phenomenon plaguing many long-running complex software systems, which exhibit performance degradation or an increasing failure rate. Several strategies based on the proactive rejuvenation of the software state have been proposed to counteract software aging and prevent failures. This survey article provides an overview of studies on Software Aging and Rejuvenation (SAR) that have appeared in major journals and conference proceedings, with respect to the statistical approaches that have been used to forecast software aging phenomena and to plan rejuvenation, the kind of systems and aging effects that have been studied, and the techniques that have been proposed to rejuvenate complex software systems. The analysis is useful to identify key results from SAR research, and it is leveraged in this article to highlight trends and open issues.

References

[1]

Adams, E. 1984. Optimizing preventive service of software products. IBM J. Res. Devel. 28, 1, 2--14.

Digital Library

[2]

Alonso, J., Belanche, L., and Avresky, D. 2011a. Predicting software anomalies using machine learning techniques. In Proceedings of the 2011 IEEE International Symposium on Network Computing and Applications (NCA'11). 163--170.

Digital Library

[3]

Alonso, J., Matias, R., Vicente, E., Carvalho, A., and Trivedi, K. 2011b. A comparative evaluation of software rejuvenation strategies. In Proceedings of the 2011 IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR). 26--31.

Digital Library

[4]

Alonso, J., Torres, J., Berral, J., and Gavaldà, R. 2010. J2ee instrumentation for software aging root cause application component determination with ASPECTJ. In Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and PhD Forum (IPDPSW'10).

[5]

Andrade, E. C., MacHida, F., Kim, D., and Trivedi, K. 2011. Modeling and analyzing server system with rejuvenation through SYSML and stochastic reward nets. In Proceedings of the 2011 6th International Conference on Availability, Reliability and Security (ARES'11). 161--168.

Digital Library

[6]

Andrzejak, A. and Silva, L. 2007. Deterministic models of software aging and optimal rejuvenation schedules. In Proceedings of the 10th IFIP/IEEE International Symposium on Integrated Network Management 2007 (IM'07). 159--168.

[7]

Andrzejak, L. and Silva, A. 2008. Using machine learning for non-intrusive modeling and prediction of software aging. In Proceedings of the IEEE Network Operations and Management Symposium.

[8]

Antunes, J. 2008. Detection and prediction of resource-exhaustion vulnerabilities. In Proceedings International Symposium on Software Reliability Engineering.

Digital Library

[9]

Araujo, J., Matos, R., Maciel, P., Matias, R., and Beicker, I. 2011a. Experimental evaluation of software aging effects on the eucalyptus cloud computing infrastructure. In Middleware.

Digital Library

[10]

Araujo, J., Matos, R., Maciel, P., Vieira, F., Matias, R., and Trivedi, K. S. 2011b. Software rejuvenation in eucalyptus cloud computing infrastructure: A method based on time series forecasting and multiple thresholds. In Proceedings of the 2011 IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR). 38--43.

Digital Library

[11]

Aung, K., Park, K., and Park, J. 2005. A model of ITS using cold standby cluster. In Digital Libraries: Implementing Strategies and Sharing Experiences. Lecture Notes in Computer Science, vol. 3815. Springer, pp. 1--10.

Digital Library

[12]

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, 1, 11--33.

Digital Library

[13]

Avritzer, A., Bondi, A., and Weyuker, E. 2007. Ensuring system performance for cluster and single server systems. J. Syst. Softw. 80, 4, 441--454.

Digital Library

[14]

Avritzer, A. and Weyuker, E. 1997. Monitoring smoothly degrading systems for increased dependability. Empir. Softw. Eng. 2, 1, 59--77.

Digital Library

[15]

Avritzer, A. and Weyuker, E. J. 2004. The role of modeling in the performance testing of e-commerce applications. IEEE Trans. Softw. Eng. 30, 12, 1072--1083.

Digital Library

[16]

Baker, M. and Sullivan, M. 1992. The recovery box: Using fast recovery to provide high availability in the UNIX environment. In Proceedings of the Summer 1992 USENIX Conference. 31--43.

[17]

Balakrishnan, M., Puliafito, A., Trivedi, K., and Viniotis, Y. 1997. Buffer losses vs. deadline violations for abr traffic in an atm switch: a computational approach. Telecommun. Syst. 7, 1--3, 105--123.

Digital Library

[18]

Bao, Y., Sun, X., and Trivedi, K. 2005. A workload-based analysis of software aging, and rejuvenation. IEEE Trans. Reliability 54, 3.

[19]

Bernstein, L. 1993. Innovative technologies for preventing network outages. AT&T Tech J. 72, 4, 4--10.

[20]

Bernstein, L. and Kintala, C. 2004. Software rejuvenation. CrossTalk 17, 8, 23--26.

[21]

Bobbio, A. and Sereno, M. 1998. Fine grained software rejuvenation models. In Proceedings of the IEEE International Computer Performance and Dependability Symposium, 1998 (IPDS'98). IEEE, 4--12.

[22]

Bobbio, A., Sereno, M., and Anglano, C. 2001. Fine grained software degradation models for optimal rejuvenation policies. Perform. Eval. 46, 1, 45--62.

Digital Library

[23]

Bond, M. and McKinley, K. 2008. Tolerating memory leaks. In Proceedings of the Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA). 109--125.

Digital Library

[24]

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

Digital Library

[25]

Candea, G., Cutler, J., Fox, A., Doshi, R., Garg, P., and Gowda, R. 2002. Reducing recovery time in a small recursively restartable system. In Proceedings of the International Conference Dependable Systems and Networks, 2002.

Digital Library

[26]

Candea, G., Kawamoto, S., Fujiki, Y., Friedman, G., and Fox, A. 2004. Microreboot—a technique for cheap recovery. In Proceedings of the Symposium on Operating Systems Design & Implementation. USENIX Association, 31--44.

Digital Library

[27]

Carrozza, G., Cotroneo, D., Natella, R., Pecchia, A., and Russo, S. 2010. Memory leak analysis of mission-critical middleware. J. Syst. Softw. 83, 9, 1556--1567.

Digital Library

[28]

Cassidy, K., Gross, K., and Malekpour, A. 2002. Advanced pattern recognition for detection of complex software aging phenomena in online transaction processing servers. In Proceedings of the International Conference Dependable Systems and Networks, 2002.

Digital Library

[29]

Castelli, V., Harper, R., Heidelberger, P., Hunter, S., Trivedi, K., Vaidyanathan, K., and Zeggert, W. 2001. Proactive management of software aging. IBM J. Res. Develop. 45, 2, 311--332.

Digital Library

[30]

Chillarege, R. 2011. Understanding Bohr-Mandel bugs through ODC triggers and a case study with empirical estimations of their field proportion. In Proceedings of the 2011 IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR). 7--13.

Digital Library

[31]

Cotroneo, D., Natella, R., Pietrantuono, R., and Russo, S. 2010. Software aging analysis of the Linux operating system. In Proceedings of the 2010 IEEE 21st International Symposium Software Reliability Engineering (ISSRE).

Digital Library

[32]

Cotroneo, D., Natella, R., Pietrantuono, R., and Russo, S. 2011a. Software aging and rejuvenation: Where we are and where we are going. In Proceedings of the 2011 IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR). 1--6.

Digital Library

[33]

Cotroneo, D., Orlando, S., Pietrantuono, R., and Russo, S. 2011b. A measurement-based ageing analysis of the JVM. Softw. Test. Verif. Reliab.

[34]

Cotroneo, D., Orlando, S., and Russo, S. 2007. Characterizing aging phenomena of the Java virtual machine. In Proceedings of the 26th IEEE International Symposium Reliable Distributed Systems, 2007.

Digital Library

[35]

Cox, B., Evans, D., Filipi, A., Rowanhill, J., Hu, W., Davidson, J., Knight, J., Nguyen-Tuong, A., and Hiser, J. 2006. N-variant systems: a secretless framework for security through diversity. In Proceedings of the 15th Conference on USENIX Security Symposium. Vol. 15. USENIX Association, 9.

Digital Library

[36]

Du, X., Qi, Y., Hou, D., Chen, Y., and Zhong, X. 2009. Modeling and performance analysis of software rejuvenation policies for multiple degradation systems. In Proceedings of the International Computer Software and Applications Conference, vol. 1, 240--245.

Digital Library

[37]

Eto, H., Dohi, T., and Ma, J. 2008. Simulation-based optimization approach for software cost model with rejuvenation. In Autonomic and Trusted Computing. Lecture Notes in Computer Science, vol. 5060. Springer, pp. 206--218.

Digital Library

[38]

Ferreira, T., Matias, R., Macedo, A., and Araujo, L. 2011. An experimental study on memory allocators in multicore and multithreaded applications. In Proceedings of the 12th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2011. 92--98.

Digital Library

[39]

Gama, K. and Donsez, D. 2008. Service coroner: A diagnostic tool for locating OSGI stale references. EUROMICRO 2008 - Proceedings of the 34th EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA'08). 108--115.

Digital Library

[40]

Garg, S., Kintala, C., Huang, Y., and Trivedi, K. 1996. Minimizing completion time of a program by checkpointing and rejuvenation. Perform. Eval. Rev. 24, 1, 252--261.

Digital Library

[41]

Garg, S., Puliafito, A., Telek, M., and Trivedi, K. 1995. Analysis of software rejuvenation using Markov regenerative stochastic Petri net. In Proceedings of the 6th International Symposium on Software Reliability Engineering, 1995.

[42]

Garg, S., Puliafito, A., Telek, M., and Trivedi, K. 1998a. Analysis of preventive maintenance in transactions based software systems. IEEE Trans. Comput. 47, 1.

Digital Library

[43]

Garg, S., van Moorsel, A., Vaidyanathan, K., and Trivedi, K. 1998b. A methodology for detection and estimation of software aging. In Proceedings of the 9th International Symposium on Software Reliability Engineering, 1998.

Digital Library

[44]

Gray, J. 1985. Why do computers stop and what can be done about it&quest; In Proceedings of the Symposium on Reliability in Distributed Software and Database Systems. 3--11.

[45]

Grottke, M., Li, L., Vaidyanathan, K., and Trivedi, K. 2006. Analysis of software aging in a web server. IEEE Trans. Reliab. 55, 3.

[46]

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

[47]

Grottke, M., Nikora, A., and Trivedi, K. 2010. An empirical investigation of fault types in space mission system software. In Proceedings of the 2010 International Conference on Dependable Systems and Networks (DSN).

[48]

Heine, D. and Lam, M. 2006. Static detection of leaks in polymorphic containers. In Proceedings of the International Conference on Software Engineering 2006. 252--261.

Digital Library

[49]

Hoffmann, G., Trivedi, K., and Malek, M. 2007. A best practice guide to resource forecasting for computing systems. IEEE Trans. Reliab. 56, 4.

[50]

Huang, Y., Arsenault, D., and Sood, A. 2006. SCIT-DNS: Critical infrastructure protection through secure DNS server dynamic updates. J. High Speed Netw. 15, 1, 5--19.

Digital Library

[51]

Huang, Y., Chung, P., Kintala, C., Liang, D., and Wang, C. 1998. NT-SWIFT: Software implemented fault tolerance on Windows NT. In Proceedings of the 1998 USENIX WindowsNT Symposium.

Digital Library

[52]

Huang, Y. and Kintala, C. 1993. Software implemented fault tolerance: Technologies and experience. In Proceedings of the 1993 IEEE International Symposium on Fault-Tolerant Computing.

[53]

Huang, Y., Kintala, C., Kolettis, N., and Fulton, N. 1995. Software rejuvenation: Analysis, module and applications. In Digest of Papers of the 25th International Symposium Fault-Tolerant Computing, 1995 (FTCS-25).

Digital Library

[54]

Huang, Y., Kintala, C. M. R., Bernstein, L., and Wang, Y.-M. 1996. Components for software fault tolerance and rejuvenation. AT&T Tech. J. 75, 2, 29--37.

[55]

Jeong, J., Seo, E., Choi, J., Kim, H., Jo, H., and Lee, J. 2010. Kal: Kernel-assisted non-invasive memory leak tolerance with a general-purpose memory allocator. Softw. Pract. Exper. 40, 8, 605--625.

Digital Library

[56]

Jia, Y.-F., Zhao, L., and Cai, K.-Y. 2008. A nonlinear approach to modeling of software aging in a web server. In Proceedings of the 15th Asia-Pacific Software Engineering Conference, 2008.

Digital Library

[57]

Jung, Y. and Yi, K. 2008. Practical memory leak detector based on parameterized procedural summaries. In Proceedings of the 7th International Symposium on Memory Management. ACM, 131--140.

Digital Library

[58]

Kajko-Mattsson, M. 2001. Can we learn anything from hardware preventive maintenance&quest; In Proceedings of the 7th IEEE International Conference on Engineering of Complex Computer Systems, 2001. IEEE, 106--111.

Digital Library

[59]

Kiciman, E. and Livshits, B. 2007. Ajaxscope: A platform for remotely monitoring the client-side behavior of web 2.0 applications. In SOSP'07 - Proceedings of 21st ACM SIGOPS Symposium on Operating Systems Principles, 17--30.

Digital Library

[60]

Kim, D., Yang, C., and Park, J. 2007. Adaptation mechanisms for survivable sensor networks against denial of service attack. In Proceedings of the 2nd International Conference on Availability, Reliability and Security (ARES'07). 575--579.

Digital Library

[61]

Kourai, K. 2010. Cachemind: Fast performance recovery using a virtual machine monitor. In Proceedings of the International Conference on Dependable Systems and Networks Workshops (DSN-W), 2010. 86--92.

Digital Library

[62]

Kourai, K. and Chiba, S. 2007. A fast rejuvenation technique for server consolidation with virtual machines. In Proceedings of the 37th International Conference on Dependable Systems and Networks, 2007.

Digital Library

[63]

Kourai, K. and Chiba, S. 2011. Fast software rejuvenation of virtual machine monitors. IEEE Trans. Depend. Secure Comput. 8, 6.

Digital Library

[64]

Koutras, V. and Platis, A. 2008. Modeling perfect and minimal rejuvenation for client server systems with heterogeneous load. In Proceedings of the 14th IEEE Pacific Rim International Symposium Dependable Computing, 2008.

Digital Library

[65]

Koutras, V. and Platis, A. 2011. Applying partial and full rejuvenation in different degradation levels. In Proceedings of the IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR), 2011. 20--25.

Digital Library

[66]

Li, L., Vaidyanathan, K., and Trivedi, K. 2002. An approach for estimation of software aging in a web server. In Proceedings of the 2002 International Symposium on Empirical Software Engineering, 2002.

Digital Library

[67]

Liu, Y., Ma, Y., Han, J. J., Levendel, H., and Trivedi, K. S. 2005. A proactive approach towards always-on availability in broadband cable networks. Comput. Commun. 28, 1, 51--64.

Digital Library

[68]

Liu, Y., Trivedi, K., Ma, Y., Han, J., and Levendel, H. 2002. Modeling and analysis of software rejuvenation in cable modem termination systems. In Proceedings of the 13th International Symposium on Software Reliability Engineering, 2002.

Digital Library

[69]

Macedo, A., Ferreira, T., and Matias, R. 2010. The mechanics of memory-related software aging. In Proceedings of the IEEE 2nd International Workshop on Software Aging and Rejuvenation (WoSAR), 2010.

[70]

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

[71]

Machida, F., Nicola, V., and Trivedi, K. 2011. Job completion time on a virtualized server subject to software aging and rejuvenation. In Proceedings of the IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR), 2011. 44--49.

Digital Library

[72]

Magalhaes, J. and Silva, L. 2010. Prediction of performance anomalies in web-applications based-on software aging scenarios. In Proceedings of the IEEE 2nd International Workshop on Software Aging and Rejuvenation (WoSAR), 2010.

[73]

Marshall, E. 1992. Fatal error: how patriot overlooked a scud. Science 255, 5050, 1347--1347.

[74]

Matias, R., Barbetta, P., Trivedi, K., and Filho, P. 2010a. Accelerated degradation tests applied to software aging experiments. IEEE Trans. Reliab. 59, 1.

[75]

Matias, R., Trivedi, K., and Maciel, P. 2010b. Using accelerated life tests to estimate time to software aging failure. In Proceedings of the IEEE 21st International Symposium on Software Reliability Engineering (ISSRE), 2010.

Digital Library

[76]

Matias Jr., R. and Filho, P. J. F. 2006. An experimental study on software aging and rejuvenation in web servers. In Proceedings of the International Computer Software and Applications Conference 1, 189--196.

Digital Library

[77]

Matos, R., Maciel, P., and Matias, R. 2011. Software aging issues on the eucalyptus cloud computing infrastructure. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics.

[78]

Myint, M. and Thein, T. 2010. Availability improvement in virtualized multiple servers with software rejuvenation and virtualization. In SSIRI 2010: Proceedings of the 4th IEEE International Conference on Secure Software Integration and Reliability Improvement. 156--162.

Digital Library

[79]

Nagarajan, A. and Sood, A. 2010. SCIT and IDS architectures for reduced data ex-filtration. In Proceedings of the International Conference on Dependable Systems and Networks Workshops (DSN-W), 2010. IEEE, 164--169.

Digital Library

[80]

Naksinehaboon, N., Taerat, N., Leangsuksun, C., Chandler, C., and Scott, S. 2010. Benefits of software rejuvenation on HPC systems. In Proceedings of the International Symposium on Parallel and Distributed Processing with Applications (ISPA'10). 499--506.

Digital Library

[81]

Nellitheertha, H. 2004. Reboot Linux faster using kexec. In developerWorks technical library.

[82]

Nguyen, Q. and Sood, A. 2009. Quantitative approach to tuning of a time-based intrusion-tolerant system architecture. In Proceedings of the 3rd Workshop Recent Advances on Intrusion-Tolerant Systems. 132--139.

[83]

Ni, Q., Sun, W., and Ma, S. 2008. Memory leak detection in sun solaris OS. In Proceedings of the International Symposium on Computer Science and Computational Technology.

Digital Library

[84]

Ning, M., Yong, Q., Di, H., Xia, P., and Ying, C. 2007. Application server aging prediction model based on wavelet network with adaptive particle swarm optimization algorithm. In Advanced Intelligent Computing Theories and Applications with Aspects of Artificial Intelligence. Lecture Notes in Computer Science, vol. 4682. Springer, pp. 14--25.

Digital Library

[85]

Novark, G., Berger, E., and Zorn, B. 2009. Efficiently and precisely locating memory leaks and bloat. In Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI). 397--407.

Digital Library

[86]

Okamura, H. and Dohi, T. 2011. A pomdp formulation of multistep failure model with software rejuvenation. In Proceedings of the IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR), 2011. 14--19.

Digital Library

[87]

Okamura, H., Miyahara, S., and Dohi, T. 2003. Dependability analysis of a transaction-based multi-server system with rejuvenation. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E86-A, 8, 2081--2090.

[88]

Okamura, H., Miyahara, S., and Dohi, T. 2005. Rejuvenating communication network system under burst arrival circumstances. IEICE Transactions on Communications E88-B, 12, 4498--4506.

[89]

Oppenheimer, D., Ganapathi, A., and Patterson, D. A. 2003. Why do internet services fail, and what can be done about it&quest; In Proceedings of the 4th Conference on USENIX Symposium on Internet Technologies and Systems (USITS'03). Vol. 4. USENIX Association, Berkeley, CA, USA, 1--1.

Digital Library

[90]

Oracle. 2012. Booting and Shutting Down Oracle Solaris on x86 Platforms. Oracle Solaris 11 Information Library.

[91]

Park, J. and Choi, B. 2012. Automated memory leakage detection in android based systems. Int. J. Control Automat. 5, 2, 35--42.

[92]

Park, K. and Kim, S. 2002. Availability analysis and improvement of active/standby cluster systems using software rejuvenation. J. Syst. Softw. 61, 2, 121--128.

Digital Library

[93]

Parnas, D. 1994. Software aging. In Proceedings of the 16th International Conference on Software Engineering. IEEE Computer Society Press, 279--287.

Digital Library

[94]

Pfening, A., Garg, S., Puliafito, A., Telek, M., and Trivedi, K. 1996. Optimal software rejuvenation for tolerating soft failures. Perform. Eval. 27--28, 491--506.

Digital Library

[95]

Robb, D. 2000. Defragmenting really speeds up windows nt machines. Spectrum IEEE 37, 9, 74--77.

Digital Library

[96]

Roeder, T. and Schneider, F. 2010. Proactive obfuscation. ACM Trans. Comput. Syst. (TOCS) 28, 2, 4.

Digital Library

[97]

RTCA. 1992. DO-178B Software considerations in airborne systems and equipment certification. Require. Tech. Concepts Aviation.

[98]

Salfner, F. and Wolter, K. 2010. Analysis of service availability for time-triggered rejuvenation policies. J. Syst. Softw. 83, 9, 1579--1590.

Digital Library

[99]

Shereshevsky, M., Crowell, J., Cukic, B., Gandikota, V., and Liu, Y. 2003. Software aging and multifractality of memory resources. In Proceedings of the 2003 International Conference on Dependable Systems and Networks, 2003.

[100]

Silva, L., Alonso, J., Silva, P., Torres, J., and Andrzejak, A. 2007. Using virtualization to improve software rejuvenation. In Proceedings of the 6th IEEE International Symposium on Network Computing and Applications (NCA'07). 33--42.

[101]

Silva, L., Alonso, J., and Torres, J. 2009. Using virtualization to improve software rejuvenation. IEEE Trans. Computs. 58, 11.

Digital Library

[102]

Silva, L., Madeira, H., and Silva, J. 2006. Software aging and rejuvenation in a soap-based server. In Proceedings of the 5th IEEE International Symposium on Network Computing and Applications (NCA'06). 56--65.

Digital Library

[103]

Sousa, P., Bessani, A., Correia, M., Neves, N., and Verissimo, P. 2010. Highly available intrusion-tolerant services with proactive-reactive recovery. IEEE Trans. Paral. Distrib. Syst. 21, 4, 452--465.

Digital Library

[104]

Sullivan, M. and Chillarege, R. 1991. Software defects and their impact on system availability—A study of field failures in operating systems. In Digest of Papers of 21st International Symposium on Fault-Tolerant Computing, 1991 (FTCS-21). IEEE, 2--9.

[105]

Sundaram, V., HomChaudhuri, S., Garg, S., Kintala, C., and Bagchi, S. 2007. Improving dependability using shared supplementary memory and opportunistic micro rejuvenation in multi-tasking embedded systems. In Proceedings of the 13th Pacific Rim International Symposium on Dependable Computing, 2007.

Digital Library

[106]

Suzuki, H., Dohi, T., Kaio, N., and Trivedi, K. 2003. Maximizing interval reliability in operational software system with rejuvenation. In Proceedings of the 14th International Symposium Software Reliability Engineering, 2003.

Digital Library

[107]

Tai, A., Alkalai, L., and Chau, S. 1999. On-board preventive maintenance: A design-oriented analytic study for long-life applications. Perform. Eval. 35, 3, 215--232.

Digital Library

[108]

Tai, A., Tso, K., Sanders, W., and Chau, S. 2005. A performability-oriented software rejuvenation framework for distributed applications. In Proceedings of the International Conference Dependable Systems and Networks, 2005.

Digital Library

[109]

Tsai, T., Vaidyanathan, K., and Gross, K. 2006. Low-overhead run-time memory leak detection and recovery. In Proceedings of the 12th Pacific Rim International Symposium Dependable Computing, 2006.

Digital Library

[110]

Vaidyanathan, K., Harper, R., Hunter, S., and Trivedi, K. 2001. Analysis and implementation of software rejuvenation in cluster systems. Perform. Eval. Rev. 29, 1, 62--71.

Digital Library

[111]

Vaidyanathan, K. and Trivedi, K. 1999. A measurement-based model for estimation of resource exhaustion in operational software systems. In Proceedings of the 10th International Symposium Software Reliability Engineering, 1999.

Digital Library

[112]

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

Digital Library

[113]

Valdes, A., Almgren, M., Cheung, S., Deswarte, Y., Dutertre, B., Levy, J., Saidi, H., Stavridou, V., and Uribe, T. 2003. An architecture for an adaptive intrusion-tolerant server. In Security Protocols Workshop. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2845. Springer, pp. 158--178.

[114]

Wang, D., Xie, W., and Trivedi, K. 2007. Performability analysis of clustered systems with rejuvenation under varying workload. Perform. Eval. 64, 3, 247--265.

Digital Library

[115]

Wang, Y.-M., Huang, Y., Vo, K.-P., Chung, P.-Y., and Kintala, C. 1995. Checkpointing and its applications. In Digest of Papers for 25th International Symposium Fault-Tolerant Computing, 1995 (FTCS-25).

Digital Library

[116]

Weimer, W. 2006. Exception-handling bugs in Java and a language extension to avoid them. In Advanced Topics in Exception Handling Techniques. Lecture Notes in Computer Science, vol. 4119. Springer, pp. 22--41.

Digital Library

[117]

Wolter, K. and Reinecke, P. 2010. Stochastic models for dependable services. Electron. Notes Theoret. Comput. Sci. 261, 5--21.

Digital Library

[118]

Xie, W., Hong, Y., and Trivedi, K. 2004. Software rejuvenation policies for cluster systems under varying workload. In Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing, 2004.

Digital Library

[119]

Xu, G., Bond, M., Qin, F., and Rountev, A. 2011. Leakchaser: Helping programmers narrow down causes of memory leaks. In Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI). 270--282.

Digital Library

[120]

Xu, G. and Rountev, A. 2008a. Precise memory leak detection for java software using container profiling. In Proceedings of the International Conference on Software Engineering. 151--160.

Digital Library

[121]

Xu, G. and Rountev, A. 2008b. Precise memory leak detection for Java software using container profiling. In Proceedings of the ACM/IEEE 30th International Conference on Software Engineering, 2008.

Digital Library

[122]

Yoshimura, T., Yamada, H., and Kono, K. 2011. Can Linux be Rejuvenated without Reboots&quest; In Proceedings of the IEEE 3rd International Workshop on Software Aging and Rejuvenation (WoSAR), 2011. 50--55.

Digital Library

[123]

Zhang, H., Wu, G., Chow, K., Yu, Z., and Xing, X. 2011. Detecting resource leaks through dynamical mining of resource usage patterns. In Proceedings of the 41st International Conference on Dependable Systems and Networks Workshops (DSN-W), 2011.

Digital Library

[124]

Zhao, J. and Trivedi, K. 2011. Performance modeling of apache web server affected by aging. In Proceedings of the 3rd International Workshop on Software Aging and Rejuvenation (WoSAR), 2011. 56--61.

Digital Library

[125]

Zhao, J., Trivedi, K., Wang, Y., and Chen, X. 2010. Evaluation of software performance affected by aging. In Proceedings of the IEEE 2nd International Workshop on Software Aging and Rejuvenation (WoSAR), 2010.

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Pietrantuono RFicco MPalmieri F(2024)Testing the Resilience of MEC-Based IoT Applications Against Resource Exhaustion AttacksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2023.326313721:2(804-818)Online publication date: Mar-2024
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Wada TYamada H(2024)Reboot-Based Recovery of Unikernels at the Component Level2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN58291.2024.00017(15-28)Online publication date: 24-Jun-2024
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Index Terms

A survey of software aging and rejuvenation studies
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
2. General and reference
  1. Cross-computing tools and techniques
    1. Reliability

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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

Issue’s Table of Contents

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Journal Family

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

Amiri MAgrawal DEl Abbadi ALoo BBarcelo PSanchez-Pi NMeliou ASudarshan S(2024)Distributed Transaction Processing in Untrusted EnvironmentsCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654684(570-579)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3626246.3654684
Pietrantuono RFicco MPalmieri F(2024)Testing the Resilience of MEC-Based IoT Applications Against Resource Exhaustion AttacksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2023.326313721:2(804-818)Online publication date: Mar-2024
https://doi.org/10.1109/TDSC.2023.3263137
Wada TYamada H(2024)Reboot-Based Recovery of Unikernels at the Component Level2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN58291.2024.00017(15-28)Online publication date: 24-Jun-2024
https://doi.org/10.1109/DSN58291.2024.00017
Hao ZDi Maio FZio E(2024)Flexible operation and maintenance optimization of aging cyber-physical energy systems by deep reinforcement learningNuclear Engineering and Technology10.1016/j.net.2023.11.05256:4(1472-1479)Online publication date: Apr-2024
https://doi.org/10.1016/j.net.2023.11.052
Jia KYu XZhang CXie WZhao DXiang J(2024)PMTT: Parallel multi-scale temporal convolution network and transformer for predicting the time to aging failure of software systemsJournal of Systems and Software10.1016/j.jss.2024.112167217(112167)Online publication date: Nov-2024
https://doi.org/10.1016/j.jss.2024.112167
Cohn M(2024)The crone and the hydra: Figuring temporal relations to aging codeJournal of Aging Studies10.1016/j.jaging.2024.10125471(101254)Online publication date: Dec-2024
https://doi.org/10.1016/j.jaging.2024.101254
Alhozaimy SMenascé DAlbanese M(2024)Resilience and performance quantification of dynamic reconfigurationFuture Generation Computer Systems10.1016/j.future.2024.05.040160(120-130)Online publication date: Nov-2024
https://doi.org/10.1016/j.future.2024.05.040
Jia KYu XZhang CXie WZhao DXiang J(2024)TTAFPred: Prediction of time to aging failure for software systems based on a two-stream multi-scale features fusion networkSoftware Quality Journal10.1007/s11219-024-09692-2Online publication date: 22-Jul-2024
https://doi.org/10.1007/s11219-024-09692-2
Engel A(2024) Principles of Systems Science (Part I ) Systems Science for Engineers and Scholars10.1002/9781394211678.ch02(30-67)Online publication date: Mar-2024
https://doi.org/10.1002/9781394211678.ch02
Yakovyna VUhrynovskyi BShakhovska N(2023)A Comprehensive Model of Android Software Aging and Rejuvenation Considering Battery SavingElectronics10.3390/electronics1207160012:7(1600)Online publication date: 29-Mar-2023
https://doi.org/10.3390/electronics12071600
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