Advertisement

Early Model-Analysis of Logistics Systems

  • Freeha Azmat
  • Laura Bocchi
  • José Luiz Fiadeiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6568)

Abstract

In logistics, as in many other business sectors, service-oriented architectures (SOAs) are offering the possibility for applications to interact with each other across languages and platforms, and for external services to be procured automatically through dedicated middleware components. In this setting, one of the critical business aspects that need to be supported is the negotiation of non-functional quantitative aspects, such as costs, leading to service-level agreements (SLAs) between business parties. In this paper, we present a formal, probabilistic approach through which services can be analysed in relation to the probability that a quality of service property is satisfied.

Keywords

Business Process Logistics System Cost Rate Enterprise Architecture Logistic Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alves, Maciel, Massa: Evaluating Supply Chains with Stochastic Models similar with Petri Nets. In: SOLI, pp. 1–6. IEEE, Los Alamitos (2007)Google Scholar
  2. 2.
    Azmat: Quantitative Analysis of Service Oriented Models. MSc Project Dissertation, Department of Computer Science, University of Leicester, UK (2010)Google Scholar
  3. 3.
    Balsamo, Di Marco, Inverardi, Simeoni: Model-based performance prediction in software development: a survey. IEEE Trans. on Software Engineering 30(5), 295–310 (2004)CrossRefGoogle Scholar
  4. 4.
    Benatallah, Casati, Toumani: Web services conversation modeling: A cornerstone for e-business automation. IEEE Internet Computing 8(1), 46–54 (2004)CrossRefGoogle Scholar
  5. 5.
    Bistarelli, Montanari, Rossi: Semiring-based constraint satisfaction and optimization. J. ACM 44(2), 201–236 (1997)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Bocchi, Fiadeiro, Gilmore, Abreu, Solanki, Vankayala: A Formal Approach to Modelling Time Properties of Service-Oriented Systems. In: Handbook of Research on Non-Functional Properties for Service-oriented Systems: Future Directions. IGI (to appear in Spring 2011), http://www.cs.le.ac.uk/srml
  7. 7.
    van Dam, Adhitya, Srinivasan, Lukszo: Critical evaluation of paradigms for modelling integrated supply chains. In: Proc. ESCAPE. Computers & Chemical Engineering, vol. 33(10), pp. 1711–1726. Elsevier, Amsterdam (2009)Google Scholar
  8. 8.
    Feng, Hong-yan: Evaluation of Logistics Service Provider Using Analytic Network Proces. ICNC 2, 227–231 (2007)Google Scholar
  9. 9.
    Fiadeiro, Lopes, Bocchi, Abreu: The Sensoria reference modelling language. In: Rigorous Software Engineering for Service-Oriented Systems. LNCS. Springer, Heidelberg (2010), http://www.cs.le.ac.uk/srml Google Scholar
  10. 10.
    Franceschini, Rafele: Quality evaluation in logistic services. International Journal of Agile Management Systems 2(1), 49–54 (2000)CrossRefGoogle Scholar
  11. 11.
    Ghiani, Laporte, Musmanno: Introducing Logistic Systems. In: Introduction to Logistics Systems Planning and Control, ch. 1. Wiley, Chichester (2004)Google Scholar
  12. 12.
    Hillston: A Compositional Approach to Performance Modelling. Cambridge University Press, Cambridge (1996)CrossRefMATHGoogle Scholar
  13. 13.
    Iacob, Jonkers: Quantitative Analysis of Enterprise Architectures. In: Interoperability of Enterprise Software and Applications, pp. 239–252. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Iacob, Jonkers: Quantitative Analysis of Service Oriented Architectures. International Journal of Enterprise Information Systems 3(1) (2007)Google Scholar
  15. 15.
    IBM Developer Works. Understanding quality of service for Web services, http://www.ibm.com/developerworks/library/ws-quality.html
  16. 16.
    Kalepu, Krishnaswamy, Loke: Reputation = f(user ranking, compliance, verity). In: Proc. ICWS, p. 200. IEEE, Los Alamitos (2004)Google Scholar
  17. 17.
    Legeza: Measurement of logistics-quality. Per. Pol. Trans. Eng. 31(1-2), 89–95 (2003)Google Scholar
  18. 18.
    Liu, Ngu, Zheng: QoS computation and policing in dynamic Web service selection. In: Proc. WWW Conference on Alternate Track Papers & Posters, ACM, New York (2004)Google Scholar
  19. 19.
    Ran: A model for Web services discovery with QoS. SIGecom Exch. 4(1), 1–10 (2003)CrossRefGoogle Scholar
  20. 20.
    The Open Service Oriented Architecture collaboration. Whitepapers and specifications, http://www.osoa.org (see also oasis-opencsa.org/sca)
  21. 21.
    Tian, Gramm, Naumowicz, Ritter, Schiller: A concept for QoS integration in Web services. In: Proc. WISEW, pp. 149–155. IEEE Computer Society, Los Alamitos (2003)Google Scholar
  22. 22.
    Tribastone: The PEPA Plug-in Project. In: Quantitative Evaluation of SysTems, pp. 53–54. IEEE, Los Alamitos (2007)Google Scholar
  23. 23.
    Xu, Cao: Logistics Service Quality Analysis Based on Gray Correlation Method. International Journal of Business and Management 3(1) (2008)Google Scholar
  24. 24.
    Yang, Wu, Li: The Empirical Research on Cluster Supply Chain Flexibility and Logistics Capacity. In: ICAL, pp. 1066–1071. IEEE, Los Alamitos (2009)Google Scholar
  25. 25.
    Vu, Hauswirth, Porto, Aberer: A Search Engine for QoS-enabled Discovery of Semantic Web Services. International Journal of Business Process Integration and Management 4(4), 244–255 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Freeha Azmat
    • 1
  • Laura Bocchi
    • 2
  • José Luiz Fiadeiro
    • 2
  1. 1.Department of EngineeringBahria UniversityIslamabadPakistan
  2. 2.Department of Computer ScienceUniversity of LeicesterUK

Personalised recommendations