A best practice guide to resource forecasting for the apache webserver

Proceedings - 12th Pacific Rim International Symposium on Dependable Computing, PRDC 2006

Volumn , Issue , 2006, Pages 183-193

  Hoffmann, Günther A ^a,b   Trivedi, Kishor S ^a   Malek, Miroslaw ^b  

^a Duke University   (United States)

^b HUMBOLDT UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SOFTWARE; FAULT TOLERANCE; MATHEMATICAL MODELS; STATISTICAL METHODS; TELECOMMUNICATION SYSTEMS; WEB SERVICES;

APACHE WEBSERVERS; RESOURCE FORECASTING;

SERVERS;

EID: 34548072278     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PRDC.2006.5     Document Type: Conference Paper

References (52)

1. Arlat J., Crouzet Y., Karlsson J., Comparison of Physical and Software- Implemented Fault Injection Techniques, IEEE Transactions on Computers, pp. 1115-1133, 2003
2. Ascher, H.E. Lin, T.-T.Y. Siewiorek, D.P., Modification of: error log analysis: statistical modeling and heuristic trend analysis, IEEE Transactions on Reliability, Vol. 41(4), 1992
3. Baum E., Haussler D., What size net gives valid generalisation?, Neural computation 1(1):151-160, 1989
4. Bishop C. M., Neural Networks for Pattern Recognition, Clarendon Press, London, 1995
5. Bobbio, Garg, Gribaudo, Horvath, Sereno, Telek, Modeling Software Systems with rejuvenation, restoration and checkpointing through fluid petri nets, Proc. 8th Int. Workshop on Petri Net and Performance Models (PNPM'99), Zaragoza, Spain, pp. 82-91, 1999
6. Bums A., Edgar S. (2000), Predicting Computation Time for Advanced Processor Architectures, ():, 2000
7. Burns A. And G. Bernat and I. Broster, A Probabilistic Framework for Schedulability Analysis, Proceedings of the Third International Embedded Software Conference, EM-SOFT, Lecture Notes in Computer Science, pp. 1-15, 2003
8. V. Castelli, R.E. Harper, P. Heidelberger, S.W. Hunter, K.S. Trivedi, K. Vaidyanathan and W.P. Zeggert, Proactive Management of Software Aging, IBM JRD, Vol 45, No. 2, pp. 311-332, 2001
9. Chen Mike , Emre Kiciman, Eugene Fratkin, Armando Fox and Eric Brewer, Pinpoint: Problem Determination in Large, Dynamic Systems, Proceedings of International Performance and Dependability Symposium, Washington, DC, 2002
10. C. Cortes and V. N. Vapnik, Support vector networks, Machine Learning, 20: 273-297, 1995
11. Crowell Jonathan, Mark Shereshevsky, Bojan Cukic, Using Fractal Analysis to Model Software Aging, Lane Department of Computer Science and Electrical Engineering, 2002
12. Edsger Wybe Dijkstra, Notes On Structured Programming, Technical Report 70-WSK-03, Technological University Eindhoven, Department of Mathematics (http://www.cs.utexas.edu/users/EWD/ewd02xx/EWD249.PDF), 1970
13. Dohi T., K. Goseva-Popstojanova and K. S. Trivedi, Analysis of Software Cost Models with Rejuvenation, Proc. of the IEEE Intl. Symp. on High Assurance Systems Engineering, HASE-2000, 2000
14. Dohi T., Goseva-Popstojanova Katerina, Trivedi Kishor S., Statistical Non-Parametric Algorithms to Estimate the Optimal Software Rejuvenation Schedule, Dept. of Industrial and Systems Engineering, Hiroshima University, Japan and Dept. of Electrical and Computer Engineering, Duke University, USA, 2000
15. Frank, P.M., Fault Diagnosis in Dynamic Systems Using Analytical and Knowledge-based Redundancy - A Survey and Some New Results, Automatica, Vol. 26, No. 3, pp. 459-474, 1990
16. Gardner Mark, Probabilistic Analysis and Scheduling of Critical Soft Real-Time Systems, PhD Thesis at University of Illinois at Urbana-Champaign, 1999
17. Garg S., A. Puliafito M. Telek and K. S. Trivedi, Analysis of Software Rejuvenation using Markov Regenerative Stochastic Petri Net, In Proc. of the Sixth IEEE Intl. Symp. on Software Reliability Engineering, Toulouse, France, 1995
18. Garg S., A. van Moorsel, K. Vaidyanathan and K. S. Trivedi, A Methodology for Detection and Estimation of Software Aging, In Proc. of the Ninth IEEE Intl. Symp. on Software Reliability Engineering, Paderborn, Germany, 1998
19. Garg S., Puliofito A., Telek M., Trivedi K., Analysis of preventive Maintenance in Transaction based Software Systems, Department of electrical & computer engineering Duke University Durham, 1998
20. Geman, S., Bienenstock, E. and Doursat, R., Neural Networks and the Bias/Variance Dilemma, Neural Computation, 4, pp. 1-58, 1992
21. Isabelle Guyon, Andre Elisseeff, An Introduction to Variable and Feature Selection, Journal of Machine Learning Research 3, 1157-1182, 2003
22. Hochreiter Sepp, Obermayer Klaus, Isabelle Guyon, Steve Gunn, Masoud Nikrav, Nonlinear Feature Selection with the Potential Support Vector Machine, Feature extraction, Foundations and Applications, Springer, 2004
23. Hoffmann G. A., A Radial Basis Function Approach to Modeling Resource Demands in Distributed Computing Systems, ISMIP - International Symposium on Multi Technology Information Processing, Taiwan, 1996
24. Hoffmann G., Failure Prediction in Complex Computer Systems:A Probabilistic Approach, PhD Thesis Humboldt University Berlin, 2005
25. Guenther Hoffmann, Miroslaw Malek, Call Availability Prediction in a Telecommunication System:A Data Driven Empirical Approach, IEEE Symposium on Reliable Distributed Systems (SRDS 2006), 2006
26. Hoffmann, Trivedi, Invariant Detection for Apache Server Systems, Duke University, NC, 2006
27. Huang Y., C. Kintala, N. Kolettis and N. Fulton, Software Rejuvenation: Analysis, Module and Applications, In Proc. of the 25th IEEE Intl. Symp. on Fault Tolerant Computing (FTCS-25), Pasadena, CA, 1995
28. Huang, Chung, Wang, Liang, NT-SwiFT: Software Implemented Fault Tolerance on Windows NT, Bell Labs, Lucent Technologies and Institute of Information Science, Academia Sinica, Proceedings of the 2nd USENIX Windows NT Symposium, 1998
29. Kapadia, Fortes, Brodley, Predictive Application-Performance Modeling in a Computational Grid Environment, Eighth IEEE International Symposium on High Performance Distributed Computing, 1999
30. Lei Li, Kalyanaraman Vaidyanathan, Kishor S. Trivedi, An Approach for Estimation of Software Aging in a Web Server , International Symposium on Empirical Software Engineering (ISESE'02), 2002
31. Li L., Vaidyanathan, Trivedi, An Approach for Estimation of Software Aging in a Web Server. Department of electrical & computer enegineering Duke University Durham, 2002
32. Bev Littlewood , Lorenzo Strigini, Software reliability and dependability: a roadmap, Proceedings of the conference on The future of Software engineering, p.175-188, Limerick, Ireland, 2000
33. Liu H., Setiono R., A Probabilistic Approach to Feature Selection - A Filter Solution, Proceedings of Machine Learning: ICML'96 - 319-327, Ban, Italy, 1996
34. MacKay D.J.C., Bayesian interpolation, Neural Computation 4(3) pg. 415-447, 1992
35. Salfner, Hoffmann, Malek, Prediction-based Software Availability Enhancement, Hot Topics Volume of the Springer Lecture Notes in Computer Science (LNCS), 2005
36. Malek, Salfner, Hoffmann, Self-Rejuvenation - an Effective Way to High Availability, international Workshop on Self-Star Properties in Complex Information Systems, University of Bologna; Bertinoro (Forl)-Italy, 2005
37. Parker T.S., Chua L.O., Practical Numerical Algorithms for Chaotic Systems, Springer Verlag, 1989
38. Patton, R.J., P.M. Frank and R.N. Clark, Fault Diagnosis in Dynamic Systems: Theory and Applications, Prentice-Hall, 1989
39. Pizza, Strigini, Bondavalli, Giandomenico, Optimal Discrimination between Transient and Permanent Faults, 3rd IEEE High Assurance System Engineering Symposium, 1998
40. Rumelhart, Hinton, Williams, Learning internal representation by error propagation, In Rumelhart, McCleland cds. Parallel Distributed Processing Volume 1, MIT Press, 1986
41. Salfner F., Tschirpke S., Malek M., Comprehensive Log-files for Autonomic Systems, IEEE Proceedings of IPDPS 2004 (International Parallel and Distributed Processing Symposium), 2004
42. Schoelkopf B., Smola A., Learning with Kernels, MIT Press, 2002
43. Shereshevsky Mark, Jonathan Crowell and Bojan Cukic, Multifractal Description of Resource Exhaustion Data in Real Time Operating System, Technical Report, West Virginia University, 2001
44. Shereshevsky Mark, Jonathan Crowell, Bojan Cukic, Vijai Gandikota, Yan Liu, Software Aging and Multifractality of Memory Resources, International Conference on Dependable Systems and Networks (DSN-2003), San Francisco, 2003
45. Terrasa Andres, Bernat Guillem, Extracting Temporal Properties from Real-Time Systems by Automatic Tracing Analysis, Technical University Valencia, Real-time systems research group University of York, 2003
46. Trivedi Kishor S., Vaidyanathan Kalyanaraman and Goseva-Popstojanova Kater, Modeling and Analysis of Software Aging and Rejuvenation, Center for Advanced Computing & Communication, Dept. of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA, 2000
47. Ulerich, N. H., & Powers, G. A., Online hasard aversion and fault diagnosis in chemical processes: the digraph/fault tree method, IEEE Transactions on Reliability 37 (2), pp. 171-177., 1988
48. Vaidyanathan K. and K. S. Trivedi, A Measurement-Based Model for Estimation of Resource Exhaustion in Operational Software Systems, In Proc. of the Tenth IEEE Intl. Symp. on Software Reliability Engineering, Boca Raton, Florida, 1999
49. Ward A., Whitt W., Predicting Response Times in Processor-Sharing Queues, Stanford University (Department of Management Science and Engineering), AT&T Labs (Shannon Laboratory), Proceedings of the Fields Institute Conference, 2000
50. Weigend A. S., Gershenfeld N. A., eds., Time Series Prediction, Proceedings of the Santa Fe Institute, Vol. XV, 1994
51. Weiss G. M., Timeweaver: a Genetic Algorithm for Identifying Predictive Patterns in Sequences of Events, Rutgers University and AT&T Labs, 1999
52. Weiss G. M., Predicting telecommunication equipment failures from sequences of network alarms, In W. Kloesgen and J. Zytkow, editors, Handbook of Data Mining and Knowledge Discovery. Oxford University Press, 2001