An architecture modeling framework for probabilistic prediction

Information Systems and e-Business Management

Volumn 12, Issue 4, 2014, Pages 595-622

  Johnson, Pontus ^a   Ullberg, Johan ^a   Buschle, Markus ^a   Franke, Ulrik ^b   Shahzad, Khurram ^a  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b SWEDISH DEFENCE RESEARCH AGENCY   (Sweden)

Author keywords

Assessment; Business properties; Object Constraint Language; Prediction; Probabilistic inference; System properties; UML

Indexed keywords

EID: 84912040897     PISSN: 16179846     EISSN: 16179854     Source Type: Journal    
DOI: 10.1007/s10257-014-0241-8     Document Type: Article

References (81)

1. Aier S, Buckl S, Franke U, Gleichauf B, Johnson P, Närman P, Schweda CM, Ullberg J (2009) A survival analysis of application life spans based on enterprise architecture models. In: Proceedings of 3rd international workshop on enterprise modelling and information systems architectures (EMISA 2009), Lecture notes in informatics, pp 141–154
2. Allen RJ (1997) A formal approach to software architecture. PhD thesis, Carnegie Mellon University, Pittsburgh, PA
3. Altman DG, Gore SM, Gardner MJ, Pocock SJ (1983) Statistical guidelines for contributors to medical journals. Br Med J 286:1489–1493
4. Bass L, Clements P, Kazman R (2003) Software architecture in practice, 2nd edn. Addison-Wesley Longman Publishing Co., Inc., Reading, MA
5. Becker S, Trifu M, Reussner R (2008) Towards supporting evolution of service-oriented architectures through quality impact prediction. In: 23rd IEEE/ACM international conference on automated software engineering-workshops, 2008. ASE Workshops 2008, IEEE, pp 77–81
6. Becker S, Koziolek H, Reussner R (2009) The palladio component model for model-driven performance prediction. J Syst Softw 82(1):3–22
7. Briand L, Labiche Y, O’Sullivan L (2003) Impact analysis and change management of uml models. In: Proceedings of the international conference on software maintenance, IEEE, pp 256–265
8. Buschle M, Johnson P, Shahzad K (2013) The enterprise architecture analysis tool–support for the predictive, probabilistic architecture modeling framework. In: Proceedings of the 19th Americas conference on information systems to appear
9. Chen D, Doumeingts G (2003) European initiatives to develop interoperability of enterprise applications: basic concepts, framework and roadmap. Ann Rev Control 27(2):153–162
10. Claunch C (2011) Cloud computing can be the singular solution for at least five use cases. Techical report, Gartner
11. Cooke R, Goossens L (2004) Expert judgement elicitation for risk assessments of critical infrastructures. J Risk Res 7(6):643–656
12. Daly LE, Bourke GJ (2008) Interpretation and uses of medical statistics. Blackwell Science Ltd, Oxford
13. Dey D, Sarkar S (1998) Psql: a query language for probabilistic relational data. Data Knowl Eng 28(1):107–120
14. Distefano S, Paci D, Puliafito A, Scarpa M (2005) Design and implementation of a performance plug-in for the argouml tool. In: Proceedings of the 23rd IASTED international multi-conference on software engineering, IASTED
15. Drury C (2007) Management and cost accounting. South-Western
16. Eclipse Modeling Framework (2011) EMF: OCL plugin for the eclipse modeling framework. http://www.eclipse.org/emf/
17. Ferrer AJ, Hernández F, Tordsson J, Elmroth E, Ali-Eldin A, Zsigri C, Sirvent R, Guitart J, Badia RM, Djemame K, Ziegler W, Dimitrakos T, Nair SK, Kousiouris G, Konstanteli K, Varvarigou T, Hudzia B, Kipp A, Wesner S, Corrales M, Forgó N, Sharif T, Sheridan C (2012) Optimis: a holistic approach to cloud service provisioning. Future Gener Comput Syst 28(1):66–77. doi:10.1016/j.future.2011.05.022
18. Franke U (2012) Optimal IT service availability: shorter outages, or fewer? IEEE Trans Netw Serv Manag 9(1):22–33. doi:10.1109/TNSM.2011.110811.110122
19. Franke U, Buschle M, Österlind M (2013a) An experiment in SLA decision-making. In: Economics of grids, clouds, systems, and services. Springer, New York, pp 256–267
20. Franke U, Holm H, König J (2013b) The distribution of time to recovery of enterprise IT services (in review)
21. Franke U, Johnson P, König J (2013c) An architecture framework for enterprise IT service availability analysis. Softw Syst Model 1–29. doi:10.1007/s10270-012-0307-3
22. Freiling FC (2008) Introduction to security metrics. In: Dependability metrics. Springer, New York, pp 129–132
23. Friedman N, Getoor L, Koller D, Pfeffer A (1999) Learning probabilistic relational models. In: Proceedings of the 16th international joint conference on artificial intelligence, vol 2. Morgan Kaufmann Publishers Inc., San Francisco, CA, pp 1300–1307
24. Gardner MJ, Altman DG (1986) Confidence intervals rather than p values: estimation rather than hypothesis testing. Br Med J (Clin Res ed) 292(6522):746–750
25. Gokhale SS (2007) Architecture-based software reliability analysis: overview and limitations. IEEE Trans Dependable Secure Comput 4(1):32–40
26. Gordijn J, Osterwalder A, Pigneur Y (2005) Comparing two business model ontologies for designing e-business models and value constellations. In: Proceedings of the 18th Bled eConference, Bled, Slovenia pp 6–8
27. Grassi V, Mirandola R, Sabetta A (2007) Filling the gap between design and performance/reliability models of component-based systems: a model-driven approach. J Syst Softw 80(4):528–558
28. Grassi V, Mirandola R, Randazzo E, Sabetta A (2008) KLAPER: an intermediate language for model-driven predictive analysis of performance and reliability. In: Rausch A, Reussner R, Mirandola R, Plášil F (eds) The common component modeling example, lecture notes in computer science, vol 5153, Springer, Heidelberg, pp 327–356. doi:10.1007/978-3-540-85289-6_13
29. Gustafsson P, Höök D, Franke U, Johnson P (2009) Modeling the IT impact on organizational structure. In: Proceedings of 13th IEEE international EDOC conference (EDOC 2009)
30. Halpern JY, Weissman V (2003) Using first-order logic to reason about policies. In: Proceedings of the IEEE computer security foundations workshop, IEEE computer society
31. Hansson H, Jonsson B (1994) A logic for reasoning about time and reliability. Formal Aspects Comput 6(5):512–535
32. Heath T, Martin R, Nguyen T (2002) Improving cluster availability using workstation validation. ACM SIGMETRICS Perform Eval Rev 30(1):217–227
33. Heckerman D, Meek C, Koller D (2004) Probabilistic models for relational data. Technical report, Microsoft
34. Holm H, Shahzad K, Buschle M, Ekstedt M (2013) P2cysemol: predictive, probabilistic cyber security modeling language (in review)
35. Jackson D (2002) Alloy: a lightweight object modelling notation. ACM Trans Softw Eng Methodol 11:256–290
36. Johnson P, Iacob ME, Välja M, van Sinderen M, Magnusson C, Ladhe T (2013) Business model risk analysis: predicting the probability of business network profitability. In: Enterprise interoperability. Springer, New York, pp 118–130
37. Joint A, Baker E, Eccles E (2009) Hey, you, get off of that cloud. Comput Law Secur Rev 25(3):270–274
38. Joseph M, Pandya P (1986) Finding response times in a real-time system. Comput J 29(5):390–395
39. Jürjens J (2002) UMLsec: extending UML for secure systems development. Lect Note Comput Sci 2460:64–87
40. Khajeh-Hosseini A, Sommerville I, Sriram I (2010) Research challenges for enterprise cloud computing. Arxiv preprint arXiv:10013257
41. Klems M, Nimis J, Tai S (2009) Do clouds compute? A framework for estimating the value of cloud computing. In: Weinhardt C, Luckner S, Stößer J, Aalst W, Mylopoulos J, Rosemann M, Shaw MJ, Szyperski C (eds) Designing E-business systems. Markets, services, and networks, lecture notes in business information processing, vol 22, Springer, Heidelberg, pp 110–123. doi:10.1007/978-3-642-01256-3_10
42. Koller D, Friedman N (2009) Probabilistic graphical models: principles and techniques. MIT Press, Cambridge, MA
43. Kurpjuweit S, Winter R (2007) Viewpoint-based meta model engineering. In: EMISA, vol 143, p 2007
44. Lee M, Kim H, Kim J, Lee J, Gum D (2005) StarUML 5.0 user guide
45. Lee JY, Lee JW, Cheun DW, Kim SD (2009) A quality model for evaluating software-as-a-service in cloud computing. In: 7th ACIS international conference on software engineering research, management and applications, 2009. SERA ’09, pp 261 –266. doi:10.1109/SERA.2009.43
46. Lodderstedt T, Basin D, Doser J (2002) SecureUML: a UML-based modeling language for model-driven security. Lect Note Comput Sci 2460:426–441
47. Lyu MR (1996) Handbook of software reliability engineering. Mcgraw-Hill, New York
48. Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A (2011) Cloud computing-the business perspective. Decis Support Syst 51(1):176–189
49. Mason-Jones R, Towill DR (1999) Total cycle time compression and the agile supply chain. Int J Prod Econ 62(1–2):61–73
50. Meedeniya I, Aleti A, Grunske L (2012) Architecture-driven reliability optimization with uncertain model parameters. J Syst Softw 85(10):2340–2355
51. Melton J, Simon A (1993) Understanding the new SQL: a complete guide. Morgan Kaufmann Publishers, Los Altos, CA
52. Milch B, Marthi B, Russell S, Sontag D, Ong DL, Kolobov A (2005) Blog: probabilistic models with unknown objects. In: Proceedings of the 19th international joint conference on artificial intelligence, Morgan Kaufmann Publishers Inc.,Los Altos, CA, IJCAI’05, pp 1352–1359
53. Moriconi M, Qian X (1994) Correctness and composition of software architectures. SIGSOFT Softw Eng Notes 19:164–174
54. Närman P, Buschle M, Ekstedt M (2012) An enterprise architecture framework for multi-attribute information systems analysis. Softw Syst Model 1–32. doi:10.1007/s10270-012-0288-2
55. Nielsen J (1994) Usability engineering. Access Online via Elsevier
56. Object Constraint Language (2010) Object Management Group, version 2.3
57. OMG Unified Modeling Language (OMG UML) (2011) Superstructure. Object Management Group, version 2.4
58. Österlind M, Johnson P, Karnati K, Lagerström R, Välja M (2013) Enterprise architecture evaluation using utility theory. In: The trends in enterprise architecture research (TEAR) workshop
59. Osterwalder A, et al (2004) The business model ontology: a proposition in a design science approach. Institut dInformatique et Organisation Lausanne, Switzerland, University of Lausanne, Ecole des Hautes Etudes Commerciales HEC 173
60. Oxford Dictionaries (2013) Oxford Dictionaries Online. http://www.oxforddictionaries.com/definition/english/system
61. Puschner P, Koza C (1989) Calculating the maximum execution time of real-time programs. Real-Time Syst 1:159–176
62. Quatrani T (2002) Visual modeling with rational rose 2002 and UML, 3rd edn. Addison-Wesley Professional, Reading, MA
63. Randles M, Lamb D, Taleb-Bendiab A (2010) A comparative study into distributed load balancing algorithms for cloud computing. In: IEEE 24th international conference on advanced information networking and applications workshops (WAINA), 2010, IEEE, pp 551–556
64. Rappaport A (2000) Creating Shareholder value: a guide for managers and investors. Free Press, New York
65. Richards C (2004) Certain to win: the strategy of John Boyd, applied to business. Xlibris Corporation
66. Ritchey R, Ammann P (2000) Using model checking to analyze network vulnerabilities. In: Proceedings on IEEE symposium on security and privacy, 2000. S P 2000. IEEE, pp 156–165
67. Rold CD, Chamberlin T (2011) Cloud sourcing deals anatomy: from public to private, from services to technology lock-in. Technical report, Gartner
68. Ross JW, Weill P, Robertson DC (2006) Enterprise architecture as strategy: creating a foundation for business execution. Harvard Business Press, London
69. Schroeder B, Gibson G (2010) A large-scale study of failures in high-performance computing systems. IEEE Trans Dependable Secur Comput 7(4):337–350
70. Skene J, Emmerich W (2003) A model-driven approach to non-functional analysis of software architectures. In: Proceedings of the 18th IEEE international conference on automated software engineering, IEEE
71. Smith CU, Williams LG (2001) Performance solutions: a practical guide to creating responsive, scalable software. Addison-Wesley Professional, Reading, MA
72. Snow A, Weckman G (2007) What are the chances an availability SLA will be violated? In: Sixth international conference on networking, 2007. ICN’07, IEEE, pp 35–35
73. Sommestad T, Ekstedt M, Johnson P (2010) A probabilistic relational model for security risk analysis. Comput Secur 29(6):659–679
74. Spivey JM (1992) The Z notation: a reference manual. Prentice Hall International (UK) Ltd., Englewood Cliffs NJ
75. Stantchev V (2009) Performance evaluation of cloud computing offerings. In: Third international conference on advanced engineering computing and applications in sciences, 2009. ADVCOMP ’09. pp 187 –192. doi:10.1109/ADVCOMP.2009.36
76. Steinberg D, Budinsky F, Merks E, Paternostro M (2008) EMF: eclipse modeling framework. Addison-Wesley Professional, Reading, MA
77. Ullberg J, Franke U, Buschle M, Johnson P (2010) A tool for interoperability analysis of enterprise architecture models using Pi-OCL. Enterprise Interoperability IV, pp 81–90
78. Ullberg J, Johnson P, Buschle M (2012) A language for interoperability modeling and prediction. Comput Ind 63(8):766–774
79. UML Profile for MARTE (2009) Modeling and analysis of real-time embedded systems. Object Management Group, version 1.0
80. van Sinderen M, Lagerström R, Ekstedt M, Johnson P (2012) Preparing the future internet for ad-hoc business networks support. In: Proceedingson 1st international workshop on architecture modeling for the future internet enabled enterprise (AMFInE)
81. Walsh B (2004) Markov chain Monte Carlo and Gibbs sampling