Wireless Personal Communications

, Volume 83, Issue 4, pp 2593–2606 | Cite as

Simplified and Improved Analytical Hierarchy Process Aid for Selecting Candidate Network in an Overlay Heterogeneous Networks



Analytical hierarchy process (AHP) is one of the pairwise comparison, attributes weight calculation approach of multiple attribute decision making aid to select the candidate network for seamless handoff in an overlay heterogeneous network. The main challenging issue in AHP is manually computing the reciprocal matrix results in an inconsistency indicated by the consistency ratio >0.1. This paper proposes a simplified and improved AHP (SI-AHP), which accepts the perceived one-dimensional linguistic values of the attributes from the decision maker. Further, SI-AHP is used to automatically compute the reciprocal matrix for the attribute weights calculation with the minimum involvement of the decision maker resulting in reduced computational time and improved consistency. The consistency ratio of SI-AHP is further improved by deriving the reciprocal matrix of pairwise comparison of any one of the attribute to others. Using the MATLAB simulations, the proposed SI-AHP is evaluated for the consistency ratio of voice and download traffic and also for 78,125 different combinations of one-dimensional linguistic values of the attributes. SI-AHP’s weight calculated for the decision attributes is used in the multiple attribute decision making approach for selecting the candidate network in an overlay heterogeneous network.


Overlay networks Multiple attribute decision making  Analytical hierarchy process Eigenvector 


  1. 1.
    Aretz, K., Haardt, M., Konhuser, W., & Mohr, W. (2001). The future of wireless communications beyond the third generation. Computer Networks, 37(1), 83–92.CrossRefGoogle Scholar
  2. 2.
    Kassar, M., Kervella, B., & Pujolle, G. (2008). An overview of vertical handover decision strategies in heterogeneous wireless networks. Computer Commuinication, 31, 2607–2620.CrossRefGoogle Scholar
  3. 3.
    Yan, X., Sekercioglu, Y. A., & Narayanan, S. (2010). A survey of vertical handover decision algorithms in fourth generation heterogeneous wireless network. Computer Networks, 54, 1848–1863.CrossRefMATHGoogle Scholar
  4. 4.
    Mrquez-Barja, J., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2011). An overview of vertical handover techniques: Algorithms, protocols and tools. Computer Communications, 34, 985–997.CrossRefGoogle Scholar
  5. 5.
    Zekri, M., Jouaber, B., & Zeghlache, D. (2012). A review on mobility management and vertical handover solutions over heterogeneous wireless networks. Computer Communication, 35, 2055–2068.CrossRefGoogle Scholar
  6. 6.
    Stevens-Navarro, E., Lin, Y., & Wong, V. W. S. (2008). An MDP-based vertical handoff decision algorithm for heterogeneous wireless networks. IEEE Transactions on Vehicular Technology, 57, 1243–1254.CrossRefGoogle Scholar
  7. 7.
    Chamodrakas, I., & Martakos, D. (2011). A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks. Applied Soft Computing, 11, 3734–3743.CrossRefGoogle Scholar
  8. 8.
    Figueira, J., Greco, S., & Ehrgott, M. (Eds.). (2005). Multiple criteria decision analysis: State of the art surveys. Boston, Dordrecht, London: Springer-Verlag.Google Scholar
  9. 9.
    Ning, F., & Zhang, P. (2012). A multiple attribute decision making-based access selection for heterogeneous WCDMA and WLAN networks. In International Conference on Affective Computing and Intelligent Interaction (ICACII-2012) (pp. 1–2).Google Scholar
  10. 10.
    Trestian, R., Ormond, O., & Muntean, G. M. (2012). Game theory-based network selection: Solutions and challenges. IEEE Communications Surveys and Tutorials, 14, 1212–1231.CrossRefGoogle Scholar
  11. 11.
    Tzeng, G.-H., & Huang, J.-J. (2011). Multiple attribute decision making: Methods and applications. Boca Raton: CRC Press, Taylor & Francis Group.Google Scholar
  12. 12.
    Behzadiana, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39, 13051–13069.CrossRefGoogle Scholar
  13. 13.
    Wang, L., & Kuo, G. S. (2013). Mathematical modeling for network selection in heterogeneous wireless networks a tutorial. IEEE Communications Surveys and Tutorials, 15, 271–292.CrossRefMATHGoogle Scholar
  14. 14.
    Zardari, N. H., Ahmed, K., Shirazi, S. M., & Yusop, Z. B. (2014). Weighting methods and their effects on multi-criteria decision making model outcomes in water resource management. Springer Briefs in Water Science and Technology. ISBN: 978-3-319-12585-5 (Print) 978-3-319-12586-2 (Online).Google Scholar
  15. 15.
    Saaty, T. L. (1990). How to make decision: The analytic hierarchy process. European Journal of Operational Research, 48, 9–26.CrossRefMATHGoogle Scholar
  16. 16.
    Saaty, T. L. (2003). Decision-making with the AHP: Why is the principal eigenvector necessary. European Journal of Operational Research, 145, 85–91.MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Saaty, T. L., & Vargas, L. G. (2012). Models, methods, concepts & applications of the analytic hierarchy process. International series in operations research & management science (Vol. 175).Google Scholar
  18. 18.
    Bernasconi, M., Choirat, C., & Seri, R. (2010). The analytic hierarchy process and the theory of measurement. Management Science, 56, 699–711.CrossRefGoogle Scholar
  19. 19.
    Sekitani, K., & Yamaki, N. (1999). A logical interpretation for the eigenvalue method in AHP. European Journal of Operational Research, 42, 219–232.MathSciNetMATHGoogle Scholar
  20. 20.
    Tan, R. R., Aviso, K. B., Huelgas, A. P., & Promentilla, M. A. B. (2014). Fuzzy AHP approach to selection problems inprocess engineering involving quantitative and qualitative aspects. Process Safety and Environmental Protection, 92(5), 467–475.CrossRefGoogle Scholar
  21. 21.
    Zhang, W. (2004). Handover decision using fuzzy MADM in heterogeneous networks. In IEEE Wireless Communications and Networking Conference (WCNC-04) (pp. 653–658).Google Scholar
  22. 22.
    Javanbarg, M. B., Scawthorn, C., Kiyono, J., & Shahbodaghkhan, B. (2012). Fuzzy AHP-based multicriteria decision making systems using particle swarm optimization. Expert Systems with Applications, 39(1), 960–966.Google Scholar
  23. 23.
    Mosadeghi, R., Warnken, J., Tomlinson, R., & Mirfenderesk, H. (2014). Comparison of fuzzy-AHP and AHP in a spatial multi-criteria decision making model for urban land-use planning. Computers, Environment and Urban Systems, 54–65.Google Scholar
  24. 24.
    Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: An AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767–4784.CrossRefGoogle Scholar
  25. 25.
    Azadeh, A., Saberi, M., Atashbar, N. Z., Chang, E., & Pazhoheshfar, P. (2013). Z-AHP: A Z-number extension of fuzzy analytical hierarchy process. In 7th IEEE International Conference on Digital Ecosystems and Technologies (DEST) (pp. 141–147).Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • B. R. Chandavarkar
    • 1
  • Ram Mohana Reddy Guddeti
    • 1
  1. 1.Department of Information TechnologyNational Institute of Technology KarnatakaSurathkal, MangaloreIndia

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