International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

QoS and Fuzzy Logic Based Routing Protocol for CRN

Author NameAuthor Details

Gagan Deep Dhand, Rohit Kumar, Rishabh, Devashish Ghildiyal,Rachna Jain

Gagan Deep Dhand[1]

Rohit Kumar[2]

Rishabh[3]

Devashish Ghildiyal[4]

Rachna Jain[5]

[1]Department of Computer Science and Engineering, Bharati Vidyapeeth's College of Engineering, New Delhi, India

[2]Department of Computer Science and Engineering, Bharati Vidyapeeth's College of Engineering, New Delhi, India

[3]Department of Computer Science and Engineering, Bharati Vidyapeeth's College of Engineering, New Delhi, India

[4]Department of Computer Science and Engineering, Bharati Vidyapeeth's College of Engineering, New Delhi, India

[5]Department of Computer Science and Engineering, Bharati Vidyapeeth's College of Engineering, New Delhi, India

Abstract

The tremendous development in wireless technologies and multimedia applications persuaded upsurge in spectrum utilization in the past. One of the adequate clarifications to overwhelm this limitation is by using Cognitive Radios (CR). These networks are likely to boost spectrum consumption professionally by permitting Secondary Users (SUs) to take advantage of the use of the approved spectrum of primary users (PUs). CR is a kind of a sensible radio that can sense the extraneous surroundings, analyze the past and build perspicacious conclusions to switch its transmission factors in step with the current state of the atmosphere. An Ad-hoc Network engaging Cognitive Radios (CR) can often be termed as Cognitive Radio Adhoc Network (CRAHN). Routing in CRAHN is not an easy mission due to spectrum availability, power, link stability, etc. Among all the parameters, the one among the best parameter for route selection is throughput. Since several applications need a high value of throughput like Audio & Video Broadcasting, Interactive audio & Video Streaming, etc. and some require the low value of throughput like E-mail, Telnet, etc. This paper design a routing strategy based on finding an optimal throughput path using fuzzy logic. To show the efficiency of a designed scheme it is compared with the shortest path routing mechanism. Our result shows that the proposed method is efficient than Shortest Spectrum.

Index Terms

Cognitive radios

Fuzzy Logic

Mamdami-Fuzzy Logic Controller

Quality of Service (QoS)

Shortest Spectrum

Reference

  1. 1.
    Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. “A survey on spectrum management in cognitive radio networks”, IEEE Communications Magazine. Copyright 2008 IEEE, 2008, pp.40-48.
  2. 2.
    Chen, D., Zhang, Q., & Jia, W. “Aggregation aware spectrum assignment in cognitive ad-hoc networks.”, In 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), 2008, pp. 1-6.
  3. 3.
    G. Cheng, W. Liu, Y. Li and W. Cheng, "Spectrum Aware On-Demand Routing in Cognitive Radio Networks," 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Dublin, 2007, pp. 571-574.
  4. 4.
    Liang, Y. C., Zeng, Y., Peh, E., & Hoang, A. T. “Sensing-throughput tradeoff for cognitive radio networks”, In 2007 IEEE International Conference on Communications, 2007, pp. 5330-5335.
  5. 5.
    Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. “Next generation dynamic spectrum access cognitive radio wireless networks: A survey”, Computer networks, Vol.50, Issue 13, 2006, pp. 2127-2159.
  6. 6.
    Akyildiz, I. F., Lee, W. Y., & Chowdhury, K. R. “CRAHNs: Cognitive radio ad hoc networks. AD hoc networks”, Vol.7, Issue 5, 2009 pp.810-836.
  7. 7.
    Letaief, K. B., & Zhang, W. “Cooperative communications for cognitive radio networks”, Proceedings of the IEEE, Vol. 97, Issue 5, 2009, pp. 878-893.
  8. 8.
    S. M. Kamruzzaman, E. Kim and D. G. Jeong, “An Energy Efficient QoS Routing Protocol for Cognitive Radio and Ad Hoc Networks” International Conference on Advance Communication Technology (ICACT), 2011, pp.344-349.
  9. 9.
    Dutta, N., Sarma, H. K. D., Srivastava, A., & Verma, S. “A SINR Based Clustering Protocol for Cognitive Radio Ad Hoc Network (CRAHN)” , International Conference on Information Technology,2009, pp. 69-75.
  10. 10.
    Letaief, K. B., & Zhang, W. “Cooperative communications for cognitive radio networks” Proceedings of the IEEE, Vol.97, Issue 5, 2009, pp. 878-893.
  11. 11.
    S. Kulkarni and S. Markande, "Comparative study of routing protocols in Cognitive Radio Networks," International Conference on Pervasive Computing (ICPC), Pune, 2015, pp. 1-5.
  12. 12.
    Ren Han and Xiaoxia Huang, "Reliable link routing in Cognitive Radio networks," 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), Wuhan, 2010, pp. 55-58.
  13. 13.
    Pradeep Kyasanur and Nitin H. Vaidya, “Protocol Design Challenges for Multi-hop Dynamic Spectrum Access Networks,” International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005, pp.645-648.
  14. 14.
    Chen, Y., Farley, T., & Ye, N., “QoS Requirements of Network Applications on the Internet” ,Information Knowledge Systems Management,Vol.4, 2004, pp.55-76.
  15. 15.
    Najafi, B., Keshavarz-Haddad, A., & Jamshidi, A., “A new spectrum path diversity routing protocol based on AODV for cognitive radio ad hoc networks,” In 7th International Symposium on Telecommunications (IST'2014), 2014, pp. 585-589, IEEE.
  16. 16.
    Cui, C., Man, H., Wang, Y., & Liu, S., “Cooperative spectrum-aware opportunistic routing in cognitive radio ad hoc networks,” In 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014, pp. 1238-1241, IEEE.
  17. 17.
    Bădoi, C. I., Croitoru, V., & Prasad, R., “IPSAG: an IP spectrum aware geographic routing algorithm proposal for multi-hop cognitive radio networks,” In 2010 8th International Conference on Communications, 2010, pp. 491-496, IEEE.
  18. 18.
    Zhou, X., Zhou, D., Kong, X., & Sheng, Q., “ACK signal based on-demand routing ,algorithm in Cognitive Radio Networks,” In 2009 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, 2009,pp. 774-779,IEEE.
  19. 19.
    Li, B., Li, D., Wu, Q. H., & Li, H., “ASAR: Ant-based spectrum aware routing for cognitive radio networks,” In 2009 International Conference on Wireless Communications & Signal Processing,2009, pp. 1-5, IEEE.
  20. 20.
    Jashni, B., Tadaion, A. A., & Ashtiani, F., “Dynamic link/frequency selection in multi-hop cognitive radio networks for delay sensitive applications,” In 2010 17th International Conference on Telecommunications, 2010, pp. 128-132, IEEE.
  21. 21.
    Kulkarni, A. R., & Agarwal, A., “Energy-efficient QoS based route management in cognitive radio networks,” In 2015 IEEE International Conference on Data Science and Data Intensive Systems, 2015, pp. 304-310, IEEE.
  22. 22.
    Song, Z., Shen, B., Zhou, Z., & Kwak, K. S., “Improved ant routing algorithm in cognitive radio networks,” In 2009 9th International Symposium on Communications and Information Technology, 2009, pp. 110-114,IEEE.
  23. 23.
    Liu, Y., Cai, L. X., & Shen, X. S., “Spectrum-aware opportunistic routing in multi-hop cognitive radio networks,” IEEE Journal on Selected Areas in Communications, Vol. 30, Issue 10, 2012, pp. 1958-1968.
  24. 24.
    Chowdhury, K. R., & Felice, M. D., “Search: A routing protocol for mobile cognitive radio ad-hoc networks,” Computer Communications, Vol. 32, Issue 18, 2009, pp.1983-1997.
  25. 25.
    Dutta, N., & Sarma, H. K. D., “A probability based stable routing for cognitive radio adhoc networks,” Wireless Networks, Vol. 23, Issue 1, 2017, pp.65-78.
  26. 26.
    H. Zhou, H. Ying, “A method for deriving the analytical structure of a broad class of typical interval type-2 mamdani fuzzy controllers,” IEEE Trans. 420 Fuzzy Syst. Vol. 21, Issue 3, 2013, pp.447–458.
  27. 27.
    El Masri, "A fuzzy-based routing strategy for multihop cognitive radio networks", International Journal of Communication Networks and Information Security, IJCNIS-2011, Vol. 3, Issue 1, 2011. pp. 74–82.
  28. 28.
    Kukreja, V., Gupta, S., & Bhushan, B. “A fuzzy-based routing protocol for cognitive radio networks” International Journal of Fuzzy Computation and Modelling, Vol. 1, Issue 1, 2014, pp. 97-122.
  29. 29.
    Castillo, O., Amador-Angulo, L., Castro, J. R., & Garcia-Valdez, M. “A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems.” Information Sciences, Vol. 354, 2016, pp.257-274.
  30. 30.
    Nagpal, C.K., & Gupta, S. “A Delay and Spectrum Aware Fuzzy Logic Based Routing Protocol for CRN” International Journal of Computer Networks and Applications, Volume 3, Issue 1, 2016, pp.16-24.
  31. 31.
    Amini, A., & Nikraz, N. “Proposing two defuzzification methods based on output fuzzy set weights" International Journal of Intelligent Systems and Applications, Vol. 8, Issue 2, 2016,pp.1-12.
  32. 32.
    Namazov, M., & Basturk, O. “DC motor position control using fuzzy proportional-derivative controllers with different defuzzification methods,” TJFS: Turkish Journal of Fuzzy Systems, Vol.1, No.1, 2010, pp.36-54.
  33. 33.
    Rohal, P., Dahiya, R., & Dahiya, P. “Study and analysis of throughput, delay and packet delivery ratio in MANET for topology based routing protocols (AODV, DSR and DSDV)” International Journal for advance research in engineering and technology, Vol.1,Issue 2, 2013,pp.54-58.
  34. 34.
    M. F. Khan, E. A. Felemban, S. Qaisar and S. Ali, "Performance Analysis on Packet Delivery Ratio and End-to-End Delay of Different Network Topologies in Wireless Sensor Networks (WSNs)," 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks, Dalian, 2013, pp. 324-329.
  35. 35.
    B.Ruxanayasmin, B.Ananda Krishna, T.Subhashini, “Minimization of Power Consumption in Mobile Adhoc Network” International Journal of Communication Networks and Information Security (IJCNIS), 2014, pp. 38-44.
  36. 36.
    Shah, S., Khandre, A., Shirole, M., & Bhole, G. “Performance evaluation of ad hoc routing protocols using NS2 simulation,” Conference of Mobile and Pervasive Computing (CoMPC), 2008, pp.167-171.
  37. 37.
    M. Youssef, M. Ibrahim, M. Abdelatif, L. Chen and A. V. Vasilakos, "Routing Metrics of Cognitive Radio Networks: A Survey," in IEEE Communications Surveys & Tutorials, Vol. 16, No. 1, 2014, pp. 92-109.
  38. 38.
    Kadhim, A. S., & Alsabbagh, H. M. “Throughput Analysis for Cognitive Radio (CR) Systems”, International Journal of Computer Networks & Communications, Vol.4, No.4, 2012, pp.211-222.
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