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An Example of Combinatorial Evolution and Forecasting of Requirements to Communication Systems

  • M. Sh. Levin
Information Technology in Engineering Systems
  • 24 Downloads

Abstract

The paper presents an analysis of the combinatorial evolution and prediction of modular systems in application to requirements to communications. A hierarchical model of the system of requirements is used (local alternative variants of modifications, their characteristics, tree-like structure over local modifications). The forecasting is based on combinatorial optimization models (hierarchical morphological design) in the form of selecting the best local modifications and combining them with allowance for their compatibility. An illustrative example describes a four-stage evolution and forecasting of a hierarchical system of requirements to the topology of a communication system.

Keywords

modular system requirements communications evolution forecasting decision making combinatorial optimization 

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References

  1. 1.
    M. R. Bhala and A. V. Bhala, “Generations of mobile wireless technology: a survey,” Int. J. Comp. Appl. 5 (4), 26–32 (2010).Google Scholar
  2. 2.
    L. Bondan, C. R. Pd. Santos, and L. Z. Granville, “Management requirements for ClickOS-based network function virtualization,” in Proc. 2014 10th Int. Conf. on Network and Service Management (CNSM), Rio de Janeiro, Brazil, Nov. 17–21, 2014 (IEEE, New York, 2014), pp. 447–450.Google Scholar
  3. 3.
    N. M. K. Chowdhury and R. Boutaba, “A survey of network virtualization,” Comp. Networks 54, 862–876 (2010).CrossRefzbMATHGoogle Scholar
  4. 4.
    N. Feamster, J. Rexford, and E. Zegura, “The road of SDN: an intellectual history of programmable networks,” ACM SIGCOMM Comput. Commun. Rev. 44 (2), 87–98 (2014).CrossRefGoogle Scholar
  5. 5.
    D. M. Ferbandez and S. Wagner, “Naming the pain in requirements engineering: A design for a global family of surveys and first results from Germany,” Inf. Software Technol. 57, 616–643 (2015).CrossRefGoogle Scholar
  6. 6.
    B. Han, V. Gopalakrishnan, L. Ji, and S. Lee, “Network function virtualization: Challenges and opportunities for innovation,” IEEE Commun. Mag. 53 (2), 90–97 (2015).CrossRefGoogle Scholar
  7. 7.
    H. Hawilo, A. Shami, M. Mirahmadi, and R. Asal, “NFV: state of the art, challenges, and implementation in next generation mobile networks (vEPC),” IEEE Networks 28 (6), 18–26 (2014).CrossRefGoogle Scholar
  8. 8.
    M. G. Kachhavay and A. P. Thakare, “5G technologyevolution and revolution,” Int. J. Comp. Sci. Mobile Comput. 3, 1080–1087 (2014).Google Scholar
  9. 9.
    I. Karakatsanis and W. AlKhader, F. MacCrory, A. Alibasic, M. Atif Omar, Z. Aung, and W.-L. Woon, “Data mining approach to monitoring the requirements of the job market: A case study,” Inf. Syst. 65, 1–6 (2017).CrossRefGoogle Scholar
  10. 10.
    Y. Koren, U. Heisel, F. Jovane, T. Moriwaki, G. Pritzschow, G. Van. Ulsoy, and H. Brussel, “Reconfigurable manufacturing systems,” CIRP Ann. Manuf. Technol. 48, 527–540 (1999).CrossRefGoogle Scholar
  11. 11.
    D. Kreutz, F. M. V. Ramos, P. E. Verissimo, C. E. Rothenberg, S. Azodolmolky, and S. Uhlig, “Software-defined networking: A comprehensive survey,” Proc. IEEE 103, 14–76 (2015).CrossRefGoogle Scholar
  12. 12.
    N. A. Kuznetsov, M. S. Levin, and V. M. Vishnevsky, “Some combinatorial optimization schemes for multilayer network topologyin,” in Electr. Proc. of 17th IMACS World Congress on Scientifics Computation, Applied Mathematics and Simulation, Paris, France, July 11–15, 2005 (Ecole Centrale de Lille, Villeneuve d’Ascq, France, 2005), Paper T4-I-42-0486.Google Scholar
  13. 13.
    M. Sh. Levin, “Hierarchical components of humancomputer systems,” in Lecture Notes in Computer Science 753 (Springer, Berlin, 1993), pp. 37–52.Google Scholar
  14. 14.
    M. Sh. Levin, Combinatorial Engineering of Decomposable Systems (Springer, 1998).CrossRefzbMATHGoogle Scholar
  15. 15.
    M. Sh. Levin, “Combinatorial evolution of composite systems,” in Proc. 16th Eur. Meeting on Cybern. and Syst. Res., Austria, 2002, Vol. 1, pp. 275–280.Google Scholar
  16. 16.
    M. Sh. Levin, Composite Systems Decisions (Springer, 2006).Google Scholar
  17. 17.
    M. Sh. Levin, “Combinatorial technological systems problems (examples for communication system)” in Proc. Int. Conf. on Systems Engineering and Modeling (ICSEM-2007), Herzliyya-Haifa, Israel, Mar. 20–23, 2007 (IEEE, New York, 2007), pp. 24–32.CrossRefGoogle Scholar
  18. 18.
    M. Sh. Levin, “Towards communication network development (structural system issues, combinatorial models)” in Proc. 2010 IEEE Region 8 Int. Conf. (SIBIRCON-2010), Irkutsk, Listvyanka, Russia, July 11–15, 2010 (IEEE, New York, 2010), Vol. 1, pp. 204–208.Google Scholar
  19. 19.
    M. Sh. Levin, “Towards combinatorial evolution of composite systems,” Expert Syst. Appl. 40, 1342–1351 (2013).CrossRefGoogle Scholar
  20. 20.
    M. Sh. Levin, Technology of Decision Support of for Modular Systems. Electronic Book (Moscow, 2013). http://www.mslevin.iitp.ru/Levin-bk-Nov2013-071.pdf.Google Scholar
  21. 21.
    M. Sh. Levin, Modular System Design and Evaluation (Sprigner, 2015).CrossRefGoogle Scholar
  22. 22.
    M. Sh. Levin, “Note on evolution and forecasting of requirements: communications example,” Electr. Preprint (May 22, 2017). http://arxiv.org/abs/1705.07558 [cs.NI].Google Scholar
  23. 23.
    M. Sh. Levin and B. J. Feldman, “System evolution: example for signal processing,” in Proc. of 14th Int. Conf. on Systems Engineering (ICSE-2000), Coventry Univ., UK, 2000 (Coventry Univ., Coventry, 2000), pp. 377–380.Google Scholar
  24. 24.
    M. Sh. Levin, O. Kruchkov, O. Hadar, and E. Kaminsky, “Combinatorial systems evolution: example of standard for multimedia information,” Informatica 20, 519–538 (2009).zbMATHGoogle Scholar
  25. 25.
    M. Sh. Levin, A. Andrushevich, R. Kistler, and A. Klapproth, “Combinatorial evolution of ZigBee protocol,” in Proc. 2010 IEEE Region 8 Int. Conf. SIBIRCON-2010 (IEEE, New York, 2010), Vol. 1, pp. 314–319.Google Scholar
  26. 26.
    M. Sh. Levin, A. Andrushevich, R. Kistler, and A. Klapproth, “Combinatorial evolution and forecasting of communication protocol ZigBee,” Electr. Preprint, (Apr. 15, 2012). http://arxiv.org/abs/1204.3259 [cs.NI].Google Scholar
  27. 27.
    P. Loucopoulos and V. Karakostas, System Requirements Engineering (McGraw Hill, 1995).Google Scholar
  28. 28.
    H. Mehta, D. Patel, B. Joshi, and H. Modi, “0G to 5G mobile technology: a survey,” J. Basic & Appl. Eng. Res. 1 (6), 56–60 (2014).Google Scholar
  29. 29.
    R. Mijumbi, J. Serrat, J.-L. Gorricho, N. Bouten, F. De Turck, and R. Boutaba, “Network function virtualization: state-of-the art and research challenges,” IEEE Commun. Surveys & Tutorials 18, 236–262 (2016).CrossRefGoogle Scholar
  30. 30.
    B. A. A. Nunes, M. Mendinca, X.-N. Nguen, K. Obraszka, T. Turletti, “A survey of software-defined networking: past, present, and future of programmable networks,” IEEE Commun. Surveys & Tutorials 16, 1617–1634 (2014).CrossRefGoogle Scholar
  31. 31.
    K. Pohl, Requirements Engineering: Fundamentals, Principles, and Techniques (Springer-Verlag, Berlin, 2010).CrossRefGoogle Scholar
  32. 32.
    P. Sharma, “Evolution of mobile wireless communication networks–1G to 5G as well future prospective of next generation communication network,” Int. J. Comp. Sci. Mobile Comput. 2, 47–53 (2013).Google Scholar
  33. 33.
    A. P. Singh, S. Nigam, and N. K. Gupta, “A study of next generation wireless network 6G,” Int. J. Innovative Res. Computer and Commun. Eng. 4, 871–874 (2007).Google Scholar
  34. 34.
    X. Wu, H. R. Sadjadpour, and J. J. Garcia-Luna-Aceves, “Modeling of topology evolutions and implication on proactive routing overhead in MANETs,” Comput. Commun. 31, 782–792 (2008).CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Inc. 2017

Authors and Affiliations

  1. 1.Kharkevich Institute for Information Transmission ProblemsRussian Academy of SciencesMoscowRussia

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