A novel vertical handover algorithm based on Adap-tive Neuro-Fuzzy Inference System (ANFIS)

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Nowadays, there is an increased demand on an Internet connection anywhere at any time. Therefore, one has to exploit all available heterogeneous wireless networks where the target is achieving the Always Best Connected (ABC) among the different networks like UMTS, WiMAX, and WLAN. So, vertical handover techniques are used to ensure the best connectivity anywhere at any time. In this paper, novel ANFIS-based vertical handover is presented and compared with TOPSIS algorithm and other algorithms as a representative of Multi-criteria decision making (MCDM) algorithm's family. The simulation results show that the proposed handover technique provided better performance in terms of minimizing the time delay and improving the quality of service (QOS). This is because ANFIS requires iterations only in training phase otherwise, it has a much faster response. Our simulations considered the effect of many practical parameters on handover, such as subscriber speed, jitter, initial delay, bandwidth and received signal strength (RSS).According to these parameters, output values produced, which is utilized to choose the best candidate access network.


  • Keywords


    Vertical Handover; TOPSIS; MADM Method; ANFIS.

  • References


      [1] Saaty TL, Decision making with the analytic hierarchy process, Int. J. Services Sciences, Vol. 1, No. 1,(2008), pp.83–98. https://doi.org/10.1504/IJSSCI.2008.017590.

      [2] Guo D, Li X, An Adaptive Vertical Handover Algorithm Based On The Analytic Hierarchy Process For Heterogeneous Networks, 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), IEEE.Zhangjiajie, China,(2015), pp. 2059- 2064.

      [3] Dan F, Ma Y, Zhou F, et al. al, A Multi-attribute Vertical Handover Algorithm Based on Adaptive Weight in Heterogeneous Wireless Network, 2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, IEEE.Guangdong, China, (2014), pp.184-188.

      [4] Bhosale S, Daruwala R, Multi-criteria Vertical Handoff Decision Algorithm Using Hierarchy Modeling and Additive Weighting in an Integrated WLAN/WiMAX/UMTS. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 81,(2014), pp.35-57.

      [5] Verma R, Singh NP, GRA-based network selection in heterogeneous wireless networks. Wireless Personal Communications, Vol. 72, NO. 2, (2013), pp. 1437-1452. https://doi.org/10.1007/s11277-013-1087-y.

      [6] Lahby M, Cherkaoui L, Adib A, Network selection algorithm based on diff-ahp and topsis in heterogeneous wireless networks, 2012 International Conference on Multimedia Computing and Systems, IEEE. Tangier, Morocco, (2012), pp. 485–490. https://doi.org/10.1109/ICMCS.2012.6320193.

      [7] Rajule N, Ambudkar B, Seamless and Optimised Vertical Handover Algorithm, 2015 International Conference on Computing Communication Control and Automation, IEEE. Pune, India, (2015), pp. 195-199. https://doi.org/10.1109/ICCUBEA.2015.43.

      [8] Alkhawini MM., Alslam KA, Hussein AA,Multi- Criteria Vertical Handover by TOPSIS and Fuzzy Logic, 2011 International Conference on Communications and Information Technology (ICCIT), IEEE. Aqaba, Jordan, (2011), pp. 96-102. https://doi.org/10.1109/ICCITECHNOL.2011.5762703.

      [9] Abraham A, Adaptation of Fuzzy Inference System Using Neural Learning, Nadia N, Luiza de MM. Fuzzy Systems Engineering: Theory and Practice, 181 Studies in Fuzziness and Soft Computing.SpringerVerlag, Germany,(2005), pp. 53–83.

      [10] ŽUNIĆ E, DJEDOVIĆ A, AVDAGIĆ Z, Decision support system for candidates classification in the employment process based on ANFIS method, 2016 XI International Symposium on Telecommunications (BIHTEL), IEEE. Sarajevo, Bosnia –Herzegovina,(2016), pp. 1-6.

      [11] Savitha K, Chandrasekar C, Vertical Handover decision schemes using SAW and WPM for Network selection in Heterogeneous Wireless Networks.Global Journal of Computer Science and Technology,Vol. 11, NO. 9, 2011.


 

View

Download

Article ID: 8592
 
DOI: 10.14419/ijet.v7i1.8592




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.