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New Manhattan distance-based fuzzy MADM method for the network selection

New Manhattan distance-based fuzzy MADM method for the network selection

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Mobile devices are increasingly developing, and more sophisticated wireless networks are available as well. Users nowadays want to access the best available technology anytime, following the always best-connected concept, which leads often to vertical handovers. It means changing the wireless access type and is an important research area in the next generation of networking. In contrast, when changing the point of attachment while using the same wireless technology, it is a ‘horizontal handover’. When handing over the communications, the transfer should be ‘seamless’, i.e. it should not cause delays or break the session and disconnect the user. Indeed, the vertical handover process is continuously improving, especially the network selection step, which is the most crucial one. Naturally, multi-attribute decision-making (MADM) methods fit this kind of issues, but they still produce some undesirable results sometimes, due to metrics imprecision and vagueness. The authors propose in this study a new network selection scheme, combining the fuzzy logic and a new MADM method, named fuzzy Manhattan distance to the ideal alternative. They compare through simulations this new technique, with the best known MADM methods, as well as with fuzzy grey relational analysis, to evaluate its performance in the same context.

References

    1. 1)
      • 1. Almutairi, A.F., Landolsi, M.A., Al-Hawaj, A.O.: ‘Weighting selection in GRA-based MADM for vertical handover in wireless networks’. IEEE Proc. UKSim-AMSS 18th Int. Conf. on Computer Modelling and Simulation (UKSim), Cambridge UK, 2016, pp. 331336.
    2. 2)
      • 2. El Helou, M., Lahoud, S., Ibrahim, M., et al: ‘A hybrid approach for radio access technology selection in heterogeneous wireless networks’, Wireless Pers Commun, 2016, 86, (2), pp. 789834, https://doi.org/10.1007/s11277-015-2957-2.
    3. 3)
      • 3. Mahardhika, G., Ismail, M., Nordin, R.: ‘Multi-criteria vertical handover decision algorithm in heterogeneous wireless network’, J. Theor. Appl. Inf. Technol., 2013, 54, (2), pp. 339345.
    4. 4)
      • 4. Gupta, V.: ‘IEEE 802.21 media independent handover. IEEE p802.21 tutorial’, 2008. Available at http://www.ieee802.org/21/Tutorials/802%2021-IEEE-Tutorial.ppt (accessed September 2018).
    5. 5)
      • 5. Bijwe, A., Dethe, C.: ‘RSS based vertical handoff algorithms for heterogeneous wireless networks – a review’, Int. J. Adv. Comput. Sci. Appl., 2011, 1, (2), pp. 6267.
    6. 6)
      • 6. Trestian, R., Ormond, O., Muntean, G.M.: ‘Game theory-based network selection: solutions and challenges’, IEEE Commun. Surv. Tutor., 2012, 14, (1), pp. 12121231.
    7. 7)
      • 7. Goudarzi, S., Hassan, W.H., Anisi, M.H., et al: ‘MDP-based network selection scheme by genetic algorithm and simulated annealing for vertical-handover in heterogeneous wireless networks’, Wirel. Pers. Commun., 2017, 92, (2), pp. 399436. Available at https://doi.org/10.1007/s11277-016-3549-5.
    8. 8)
      • 8. Kumar, D., Singh, J., Singh, O.P., et al: ‘A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices’, Math. Comput. Model., 2013, 57, (11), pp. 29452960. Information system security and performance modeling and simulation for future mobile networks. Available at http://www.sciencedirect.com/science/article/pii/S0895717713000769.
    9. 9)
      • 9. Kelemenis, A., Ergazakis, K., Askounis, D.: ‘Support managers’ selection using an extension of fuzzy topsis', Expert Syst. Appl., 2011, 38, (3), pp. 27742782.
    10. 10)
      • 10. Prithiviraj, A., Krishnamoorthy, K., Vinothini, B.: ‘Fuzzy logic based decision making algorithm to optimize the handover performance in Hetnets’, Circuits Syst., 2016, 07, (11), pp. 37563777.
    11. 11)
      • 11. Mansouri, M., Leghris, C: ‘The use of MADM methods in the vertical handover decision making context’. IEEE Proc. Int. Conf. on Wireless Networks and Mobile Communications (WINCOM 2017), Rabat, Morocco, 2017, pp. 16.
    12. 12)
      • 12. Verma, R., Singh, N.: ‘GRA based network selection in heterogeneous wireless networks’, Wirel. Pers. Commun., 2013, 72, pp. 14371452.
    13. 13)
      • 13. Mansouri, M., Leghris, C.: ‘An adaptation of GRA method for network selection in vertical handover context’. Advances in Intelligent Systems and Computing. Int. Conf. on Information Technology and Communication Systems (ITCS), Khouribga, Morocco, 2017, vol. 640, pp. 171179.
    14. 14)
      • 14. Chinnappan, A., Balasubramanian, R.: ‘Complexity–consistency trade-off in multi-attribute decision making for vertical handover in heterogeneous wireless networks’, IET Netw., 2016, 5, pp. 1321. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-net.201 5.0042.
    15. 15)
      • 15. Chandavarkar, B.R., Guddeti, R.M.R.: ‘Simplified and improved multiple attributes alternate ranking method for vertical handover decision in heterogeneous wireless networks’, Comput. Commun, 2016, 83, (C), pp. 8197. Available at http://dx.doi.org/10.1016/j.comcom.2015.10.011.
    16. 16)
      • 16. Lahby, M., Leghris, C., Adib, A.: ‘A novel ranking algorithm based network selection for heterogeneous wireless access’, J. Netw., 2013, 8, (2), pp. 263272.
    17. 17)
      • 17. Skondras, E., Sgora, A., Michalas, A., et al: ‘An analytic network process and trapezoidal interval-valued fuzzy technique for order preference by similarity to ideal solution network access selection method’, Int. J. Commun. Syst., 2014, 29, (2), pp. 307329.
    18. 18)
      • 18. Mansouri, M., Leghris, C.: ‘Using fuzzy gray relational analysis in the vertical handover process in wireless networks’. 5th Int. Conf. on Networked Systems (NETYS 2017), Marrakech, Morocco, 2017, pp. 396401.
    19. 19)
      • 19. Chamodrakas, I., Martakos, D.: ‘A utility-based fuzzy topsis method for energy efficient network selection in heterogeneous wireless networks’, Appl. Soft Comput., 2012, 12, (7), pp. 19291938.
    20. 20)
      • 20. Kassar, M., Kervella, B., Pujolle, G.: ‘An overview of vertical handover decision stratgies in heterogeneous wireless networks’, Comput. Commun., 2008, 31, pp. 26072620.
    21. 21)
      • 21. Bhute, H., Karde, P.P., Thakare, V.M.: ‘A vertical handover decision approaches in next generation wireless networks: a survey’, Int. J. Mob. Netw. Commun. Telemat., 2014, 4, (2), pp. 3343.
    22. 22)
      • 22. Ferretti, S., Ghini, V., Panzieri, F.: ‘A survey on handover management in mobility architectures’, Comput. Netw., 2016, 94, (C), pp. 390413.
    23. 23)
      • 23. Obayiuwana, E., Falowo, O.E.: ‘Network selection in heterogeneous wireless networks using multi-criteria decision-making algorithms: a review’, Wirel. Netw., 2016, 23, (8), pp. 26172649.
    24. 24)
      • 24. Stevens-Navarro, E., Wong, V.W.S.: ‘Comparison between vertical handoff decision algorithms for heterogeneous wireless networks’. IEEE Proc. IEEE Conf. Vehicular Technology (VTC-2006), Montreal, Que., Canada, 2006, pp. 947951.
    25. 25)
      • 25. Fernandes, S., Karmouch, A.: ‘Vertical mobility management architectures in wireless networks: a comprehensive survey and future directions’, IEEE Commun. Surv. Tutor., 2012, 14, (1), pp. 4563.
    26. 26)
      • 26. Gumus, A., Yayla, Y., Celik, E., et al: ‘A combined fuzzy-AHP and fuzzy-GRA methodology for hydrogen energy storage method selection in Turkey’, Energies, 2013, 6, (6), pp. 30173032.
    27. 27)
      • 27. Büyüközkan, G., Çifçi, G.: ‘A novel hybrid MCDM approach based on fuzzy dematel, fuzzy ANP and fuzzy topsis to evaluate green suppliers’, Expert Syst. Appl., 2012, 39, (3), pp. 30003011.
    28. 28)
      • 28. Wang, L., Kuo, G.G.S.: ‘Mathematical modeling for network selection in less networks – a tutorial’, IEEE Commun. Surv. Tutor., 2013, 15, (1), pp. 271292.
    29. 29)
      • 29. Saaty, T.: ‘Decision making with the analytic hierarchy process’, Int. J. Serv. Sci., 2008, 1, pp. 8398.
    30. 30)
      • 30. Saaty, T.: ‘Fundamentals of the analytic network process-dependence and feedback in decision-making with a single network’, J. Syst. Sci. Syst. Eng., 2004, 13, pp. 129157.
    31. 31)
      • 31. Ramanayaka, K.H.: ‘Application of extent analysis fahp to determine the relative weights of evaluation indices for library website usability acceptance model’, IET Softw., 2019, 13, pp. 8695. Available at https://digital-library.theiet.org/content/journals/10.1049/iet-sen.201 8.5185.
    32. 32)
      • 32. Do, Q.H., Chen, J.F.: ‘A hybrid fuzzy AHP-DEA approach for assessing university performance’, WSEAS Trans. Bus. Econ., 2014, 11, pp. 386397.
    33. 33)
      • 33. Wang, Y.M., Chin, K.S.: ‘Fuzzy analytic hierarchy process: a logarithmic fuzzy preference programming methodology’, Int. J. Approx. Reason., 2011, 52, (4), pp. 541553.
    34. 34)
      • 34. Liu, H.T., Wang, C.H.: ‘An advanced quality function deployment model using fuzzy analytic network process’, Appl. Math. Model., 2010, 34, (11), pp. 33333351.
    35. 35)
      • 35. Dargi, A., Anjomshoae, A., Galankashi, M.R., et al: ‘Supplier selection: a fuzzy-ANP approach’, Proc. Comput. Sci., 2014, 31, pp. 691700.
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