Using quantitative analysis to implement autonomic IT systems

Proceedings - International Conference on Software Engineering

Volumn , Issue , 2009, Pages 100-110

  Calinescu, Radu ^a   Kwiatkowska, Marta ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE MANAGEMENT; ADAPTIVENESS; AUTONOMIC ARCHITECTURE; DATA CENTRES; DISK DRIVE; DYNAMIC POWER MANAGEMENT; IN-LINE; IT SYSTEM; MARKOV CHAIN; QUANTITATIVE ANALYSIS; RAPID CHANGES; REAL-WORLD SYSTEM; SOFTWARE FRAMEWORKS; SYSTEM WORKLOADS;

ELECTRIC POWER MEASUREMENT; ENERGY MANAGEMENT; INFORMATION TECHNOLOGY; MARKOV PROCESSES;

COMPUTER SOFTWARE;

EID: 77949879210     PISSN: 02705257     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSE.2009.5070512     Document Type: Conference Paper

References (31)

1. A. Aziz et al. Model checking continuous time Markov chains. ACM Transactions on Computational Logic, 1(1):162-170, 2000.
2. R. Calinescu. Model-driven autonomic architecture. In Proc. 4th IEEE Intl. Conf. Autonomic Computing, 2007.
3. R. Calinescu. Implementation of a generic autonomic framework. In D. Greenwood et al., editor, Proc. 4th Intl. Conf. Autonomic and Autonomous Systems, pages 124-129, 2008.
4. R. Calinescu and J. Hill. System providing methodology for policy-based resource allocation, July 2004. United States Patent Application no. 10/710322.
5. R. Das et al. Towards commercialization of utility-based resource allocation. In Proc. 3rd IEEE Intl. Conf. Autonomic Computing, pages 287-290, 2006.
6. S. Ghanbari et al. Adaptive learning of metric correlations for temperature-aware database provisioning. In Proc. 4th IEEE Intl. Conf. Autonomic Computing, June 2007.
7. D. Gracanin et al. Towards a model-driven architecture for autonomic systems. In Proc. 11th IEEE Intl. Conf. Engineering of Computer-Based Systems, pages 500-505, 2004.
8. L. Grunske. Specification patterns for probabilistic quality properties. In Proc. 30th Intl. Conf. Software Engineering, pages 31-40, 2008.
9. H. Hansson and B. Jonsson. A logic for reasoning about time and reliability. Formal Aspects Comp., 6(5):512-535, 1994.
10. B. Haverkort et al. On the use of model checking techniques for dependability evaluation. In Proc. 19th IEEE Symp. Reliable Distributed Systems, pages 228-237, October 2000.
11. M. Hinchey et al. Modeling for NASA autonomous nanotechnology swarm missions and model-driven autonomic computing. In Proc. 21st Intl. Conf. Advanced Networking and Applications, pages 250-257, 2007.
12. IBM Corporation. An architectural blueprint for autonomic computing, 2004. http://www-03.ibm.com/autonomic/pdfs/ACBP2 2004-10-04.pdf.
13. D. Jansen et al. How fast and fat is your probabilistic model checker? An experimental comparison. In K. Yorav, editor, Hardware and Software: Verification and Testing, volume 4489 of LNCS, pages 69-85. Springer, 2008.
14. H. Kasinger and B. Bauer. Towards a model-driven software engineering methodology for organic computing systems. In Proc. 4th Intl. Conf. Computational Intelligence, pages 141-146, July 2005.
15. J. Kephart and D. Chess. The vision of autonomic computing. IEEE Computer Journal, 36(1):41-50, January 2003.
16. M. Kwiatkowska. Quantitative verification: Models, techniques and tools. In Proc. 6th Joint Meeting of the European Software Engineering Conf. and the ACM SIGSOFT Symp. Foundations of Software Engineering, pages 449-458. ACM Press, September 2007.
17. M. Kwiatkowska et al. Stochastic model checking. In M. Bernardo and J. Hillston, editors, Formal Methods for the Design of Computer, Communication and Software Systems: Performance Evaluation, pages 220-270. Springer, 2007.
18. M. Kwiatkowska et al. Quantitative analysis with the probabilistic model checker PRISM. Electronic Notes in Theoretical Computer Science, 153(2):5-31, 2005.
19. C. Lefurgy et al. Server-level power control. In Proc. 4th IEEE Intl. Conf. Autonomic Computing, June 2007.
20. Microsoft Corporation. XML schema definition tool, 2007. msdn2.microsoft.com/en-us/library/x6c1kb0s(VS.80).aspx.
21. R. Murch. Autonomic Computing. IBM Press, 2004.
22. M. Parashar and S. Hariri. Autonomic Computing: Concepts, Infrastructure & Applications. CRC Press, 2006.
23. J. Pena et al. A model-driven architecture approach for modeling, specifying and deploying policies in autonomous and autonomic systems. In Proc. 2nd IEEE Intl. Symp. Dependable, Autonomic and Secure Computing, pages 19-30, 2006.
24. PRISM Case Studies: Dynamic Power Management. http://www. prismmodelchecker.org/casestudies/power.php.
25. Q. Qiu et al. Stochastic modeling of a power-managed system: construction and optimization. In Proc. Intl. Symp. Low Power Electronics Design, pp. 194-199. ACM Press, 1999.
26. M. Rohr et al. Model-driven development of self-managing software systems. In Proc. 9th Intl. Conf. Model-Driven Engineering Languages and Systems. Springer, 2006.
27. SAXON - The XSLT and XQuery Processor. http://saxon.sourceforge.net/.
28. J. Sobel and D. Friedman. An introduction to reflection-oriented programming. In Proc. Reflection'96. 1996.
29. R. Sterritt and M. Hinchey. Biologically-inspired concepts for self-management of complexity. In Proc. 11th IEEE Intl. Conf. Eng. Complex Computer Systems, pages 163-168, 2006.
30. W. Walsh et al. Utility functions in autonomic systems. In Proc. 1st Intl. Conf. Autonomic Computing, pp. 70-77, 2004.
31. S. White et al. An architectural approach to autonomic computing. In Proc. 1st IEEE Intl. Conf. Autonomic Computing, pages 2-9. IEEE Computer Society, 2004.