Network Selection by Vertical Handoff in Heterogeneous Vehicular Network Using Fuzzy MADM-TOPSIS

  • Sangama Bhadouria
  • Rakesh Roshan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 472)


The prime requirements of vertical handoff in the heterogeneous vehicular network are to ensure the quality of service requirements and to provide seamless connectivity to all mobile stations. In this research paper, Multiple Attribute Decision Making (MADM) classical methods are used like the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to make the handoff decisions process quickly and efficiently. Our method called ‘MADM-TOPSIS Scheme’ is the fusing of TOPSIS method with Fuzzy Logic Sets and Rules, in order to lessen the Blocking Probability. Performance results are thus compared with the classical fuzzy TOPSIS and with an approach of the base paper. Our work is able to determine properly that by reducing the blocking probability, the handoff probability will increase that will improve the network performance in the heterogeneous vehicular system. After differentiating to classical Fuzzy TOPSIS, our work scheme shows an upgrade of 0.10 and 20% with base paper.


Vertical handover decision MADM-TOPSIS Fuzzy logic Handover probability Blocking probability 


  1. 1.
    Rikli, N-E (2012) Design of a fuzzy based handover function for mobile terminal with real time traffic over heterogeneous wireless networks. In: 2012 IEEE international conference on wireless information technology and systems (ICWITS), Nov 2012, pp 1–4Google Scholar
  2. 2.
    Thumthawatworn T, Tillapart P (2015) Enhanced fuzzy-based handover decision system design for wireless mobile networks. In: 2015 seventh international conference on ubiquitous and future networks in IEEE explorer, Sapporo, pp 491–496Google Scholar
  3. 3.
    Boussen S, Tabbane N, Tabbane S, Krief F (2014) A context aware vertical handover decision approach based on fuzzy logic. In: fourth international conference on communications and networking, ComNet-2014 in IEEE explorer, Hammamet, pp 1–5Google Scholar
  4. 4.
    Ben Zineb A, Ayadi M, Tabbane S (2015) Fuzzy MADM based vertical handover algorithm for enhancing network performances. In: 2015 23rd international conference on software, telecommunications and computer networks (SoftCOM), Split in IEEE explorer, pp 153–159Google Scholar
  5. 5.
    Diaba SY, Emmanuel A, Oyibo AM (2015) Performance analysis of queuing priority schemes in cellular communication. Int J Adv Res Comput Commun Eng 4(1):232–236.
  6. 6.
    Siddiqui AF, Kumar P, Tiwari RG (2016) Reducing handoff blocking probability in wireless cellular networks using auxiliary stations and TDMA, 1249–1253 Impact Factor value: 4.45, ISO 9001:2008 Certified JournalGoogle Scholar
  7. 7.
    Ning L, Wang Z, Guo Q, Jiang K (2013) Fuzzy clustering based group vertical handover decision for heterogeneous wireless networks. In: 2013 IEEE wireless communications and networking conference (WCNC), Shanghai, pp 1231–1236Google Scholar
  8. 8.
    Tie L, Liao H, Du Z (2006) A vertical handover decision algorithm based on fuzzy control theory. In: International multi-symposiums on IEEE—computer and computational sciences, vol 2, pp 309–313Google Scholar
  9. 9.
    Monil MAH, Qasim R, Rahman RM (2013) Speed and direction based fuzzy handover system. In: 2013 IEEE international conference on fuzzy systems (FUZZ-IEEE), Hyderabad, pp 1–8Google Scholar
  10. 10.
    Aziz A, Rizvi S, Saad NM (2010) Fuzzy logic based vertical handover algorithm between LTE and WLAN. In: IEEE 2010 international conference on intelligent and advanced systems, Kuala Lumpur, Malaysia, pp 1–4Google Scholar
  11. 11.
    Parsian S (2006) Decision making in next generation networks using fuzzy systems. Iran Telecommunication Research CenterGoogle Scholar
  12. 12.
    P. Munoz, Barco R, de la Bandera I, Toril M, Luna-Ramirez S (2011) Optimization of a fuzzy logic controller for handover-based load balancing. In: 2011 IEEE 73rd vehicular technology conference (VTC Spring), Budapest, pp 1–5Google Scholar
  13. 13.
    Deswal S, Gupta D (2015) Effective network handover using fuzzy inference for heterogeneous mobility management. Int J Sci Eng Technol Res (IJSETR) 4(7):2379–2382Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Pranveer Singh Institute of TechnologyKanpurIndia

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