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An integrated service model to support user specific QoS routing in cognitive radio ad hoc network

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Abstract

Routing in Cognitive Radio Ad Hoc Network (CRAHN) is a challenging task due to limited spectrum availability. To overcome this problem several researchers have proposed various routing schemes based on Quality of Service (QoS) and spectrum availability. These schemes choose a path that gives maximum QoS and spectrum level ignoring the required QoS level for a particular application which may be quite less than the maximum level. Thus, this paper proposes an integrated service model having eight classes instead of two for CRAHN to envisage the admission control at Primary User (PU) nodes thus reducing overhead on Secondary Users (SU) for various applications. The PU node first examines the spectrum availability and then checks whether the received packet can be granted user specific Quality of Service (QoS) or not to support Elastic plus Real Time Applications for (SU) nodes. To prove the efficacy of proposed scheme comparison with Cognitive Ad hoc On-demand Distance Vector (CAODV) or shortest spectrum aware path routing mechanism is done. The result exhibits that high performance rate for good reliability, low latency and high throughput with fair load distribution among all the nodes of the network.

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References

  1. Wireless RF Spectrum scarcity, what about light wave? (10th December 2018). Retrieved from https://www.cablelabs.com/wireless-rf-spectrum-scarcity-what-about-light-wave/

  2. Strużak R, Tjelta T, Borrego JP (2016) On radio-frequency Spectrum management. J Telecommun Inform Technol 3:108–130

    Google Scholar 

  3. Amjad M, Rehmani MH, Mao S (2018) Wireless multimedia cognitive radio networks: a comprehensive survey. IEEE Commun Surveys Tutor 20(2):1056–1103

    Article  Google Scholar 

  4. Das, S. C. Ghosh, N. Das and A. Das Barman, "Cooperative Spectrum Mobility In Heterogeneous Opportunistic Networks Using Cognitive Radio," 2015 IEEE 40th conference on local computer networks (LCN), Clearwater Beach, FL, 2015, pp. 402–405

  5. N. Joshi and J. Agarkhed, "Path construction using cognitive radio sensing in Wireless sensor network", International Conference on Circuit, Power and Computing Technologies (ICCPCT), Nagercoil, 2016, pp.1–4

  6. Yu YC, Hu L, Li HT, Zhang YM, Wu FM, Chu JF (2014) The security of physical layer in cognitive radio networks. J Commun 9(12):28–33

    Google Scholar 

  7. Wang Y, Zheng G, Ma H, Li Y, Li J (2018, 2018) A Joint Channel selection and routing protocol for cognitive radio network. Wirel Commun Mob Comput:1–7

  8. Guirguis, A., Karmoose, M., Habak, K., El-Nainay, M., & Youssef, M. “Cooperation-Based Routing In Cognitive Radio Networks”, arXiv preprint arXiv: 1608.01632, 2016, pp.1–15

  9. Hashem M, Barakat S, Alla MA (2016) A Tree Routing Protocol for Cognitive Radio Network. Egyptian Informatics J 18(2):95–103

    Article  Google Scholar 

  10. Chowdhury KR, Akyildiz IF (2011) CRP: A Routing Protocol for Cognitive Radio Ad-Hoc Networks. IEEE J Select Areas Commun 29(4):794–804

    Article  Google Scholar 

  11. B. Najafi, A. Keshavarz-Haddad and A. Jamshidi, "A New Spectrum Path Diversity Routing Protocol Based on Aodv For Cognitive Radio Ad Hoc Networks," 7th International Symposium on Telecommunications (IST 2014), Tehran, 2014, pp. 585–589

  12. L. T. Dung and B. An, "a stability-based Spectrum-aware routing protocol in Mobile cognitive radio ad-hoc networks,"international symposium on computer, Consumer and Control, Taichung, 2014, pp. 1014–1017

  13. M. Yosra, A. Mohamed and T. Sami, "QSTOD On-Demand Routing Protocol for Cognitive Radio Ad-Hoc Networks," 2016 2nd international conference on advanced Technologies for Signal and Image Processing (ATSIP), Monastir, 2016, pp. 737–740

  14. R. N. Yadav and R. Misra, "Multipath Routing Protocols in Cognitive Radio Networks," 2014 Annual IEEE India conference (INDICON), Pune, 2014, pp. 1–6

  15. N. Dutta, H. K. D. Sarma and A. K. Srivastava, "A Multipath Routing Protocol for Cognitive Radio Adhoc Networks (CRAHNs)," 2015 International conference on advances in Computing, communications and informatics (ICACCI), Kochi, 2015, pp. 1960–1965

  16. F. A. Mahgoub, H. A. Elsayed and S. El Ramly, "Performance Comparison of CAODV, SEARCH, and WCETT Routing Protocols in CRAHNs," 2016 International conference on systems informatics, Modelling and simulation (SIMS), Riga, 2016, pp. 141–146

  17. Q. Chen, L. Wang, Y. Gao, R. Chai and X. Huang, "Energy Efficient Constrained Shortest Path First-Based Joint Resource Allocation and Route Selection for Multi-Hop CRNs," in China Communications, Vol. 14, No. 12, December 2017, pp. 72–86

  18. Zareei M, Mahmoud Mohamed E, Anisi MH, Vargas Rosales C, Tsukamoto K, Khurram Khan M (2016) On-demand hybrid routing for cognitive radio ad-hoc network. IEEE Access 4:8294–8302

    Article  Google Scholar 

  19. N Shirke, K Patil, S Kulkarni and S Markande, "Energy Efficient Cluster Based Routing Protocol for Distributed Cognitive Radio Network," 2014 First international conference on Networks & Soft Computing (ICNSC 2014), Guntur, 2014, pp. 60–65

  20. Dutta N, Sarma HK (2017) A probability based stable routing for cognitive radio ad-hoc networks. J Wireless Networks 23(1):65–78

    Article  Google Scholar 

  21. M. Yosra, A. Mohamed and T. Sami, "Cognitive Qos-On Demand Routing Protocol (Co-Qorp) In Cognitive Radio Ad-Hoc Network," 2016 International symposium on networks, computers and communications (ISNCC), Yasmine Hammamet, 2016, pp. 1–4

  22. Jai Sukh Paul Singh, Mritunjay Kumar Rai, “CROP: Cognitive Radio Routing Protocol for Link Quality Channel Diverse Cognitive Networks,” Journal of Network and Computer Applications, Vol.104, 2017, pp. 48–60

  23. Saleem Y, Yau KA, Mohamad H, Ramli N, Rehmani MH, Ni Q (2017) Clustering and Reinforcement-Learning-Based Routing for Cognitive Radio Networks. IEEE Wireless Commun 24(4):146–151

    Article  Google Scholar 

  24. Ye, H., Tan, Z., Xu, S., &Qiao, X. “Load Balancing Routing in Cognitive Radio Ad Hoc Networks”,Microwave, Antenna, Propagation, and EMC Technologies for Wireless Communications (MAPE), 2011 IEEE 4th International Symposium, 2011,pp. 442–446

  25. Tang, X., Zhou, J., Xiong, S., Wang, J., & Zhou, K. “Geographic Segmented Opportunistic Routing in Cognitive Radio Ad Hoc Networks Using Network Coding”. IEEE Access, 2018, pp.1–18

  26. Xu Y, Ren J, Wang G, Zhang C, Yang J, Zhang Y (June 2019) A Blockchain-based non repudiation network Computing service scheme for industrial IoT. IEEE Trans Indust Inform 15(6):3632–3641

    Article  Google Scholar 

  27. Wang Z (2001) Internet QoS: Architectures and Mechanisms for Quality of Service, 1st edn. Morgan Kaufmann, San Francisco

    Google Scholar 

  28. McAssey, M. P., &Samaniego, F. J., “Network Reliability: A Fresh Look at Some Basic Questions”, 2011, pp.1–17

  29. Boland, P. J., Samaniego, F. J., &Vestrup, E. M. “On Computing and Comparing the Reliability of Competing Networks”, pp.1–7

  30. Kadhim AS, Alsabbagh HM (2012) Throughput analysis for cognitive radio (CR) systems. Int J Comput Netw Commun 4(4):211–222

    Article  Google Scholar 

  31. Perkins, C., Belding-Royer, E., & Das, S. “Ad Hoc On-Demand Distance Vector (AODV) routing”, 2003 (No. RFC 3561)

  32. K. R. Chowdhury, M. Di Felice and I. F. Akyildiz, "TCP CRAHN: A Transport Control Protocol for Cognitive Radio Ad Hoc Networks", in IEEE Transactions on Mobile Computing, Vol. 12, No. 4, 2013, pp. 790–803

  33. Chunsheng Xin, Bo Xie and Chien-Chung Shen, "A Novel Layered Graph Model for Topology Formation And Routing In Dynamic Spectrum Access Networks," First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN2005., Baltimore, MD, USA, 2005, pp. 308–317

  34. R. Urgaonkar and M. J. Neely, "opportunistic scheduling with reliability guarantees in cognitive radio networks," IEEE INFOCOM 2008-the 27th conference on computer communications, Phoenix, AZ, 2008, pp. 1301–1309

  35. B. Li, D. Li, Q. H. Wu and H. Li, “ASAR: Ant-Based Spectrum Aware Routing for Cognitive Radio Networks”, published in the proceedings of IEEE International Conference on Wireless Communications and Signal Processing, 2009, pp. 1–5

  36. L. Ding, T. Melodia, S. Batalama, and J. D. Matyjas, “ROSA: Distributed Joint Routing and Dynamic Spectrum Allocation in Cognitive Radio Ad Hoc Networks”, published in the proceedings of 12th ACM International conference on modelling analysis and simulation of wireless and mobile systems, 2009,pp. 13–20

  37. J Chen, H Li and J Wu, “WHAT: A Novel Routing Metric for Multi-Hop Cognitive Wireless Networks”, published in the proceedings of 19th Annual Wireless and Optical Communications Conference, 2010, pp. 1–6

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Authors and Affiliations

  1. J. C. Bose University of Science and Technology, YMCA, Faridabad, India

    Hardik Dhingra, Rashmi Chawla & Shailender Gupta

  2. Bharati Vidyapeeth’s College of Engineering, New Delhi, PaschimVihar, India

    Gagan Deep Dhand

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  1. Hardik Dhingra
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  2. Gagan Deep Dhand
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  3. Rashmi Chawla
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  4. Shailender Gupta
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Correspondence to Shailender Gupta.

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Dhingra, H., Dhand, G.D., Chawla, R. et al. An integrated service model to support user specific QoS routing in cognitive radio ad hoc network. Peer-to-Peer Netw. Appl. 14, 18–29 (2021). https://doi.org/10.1007/s12083-020-00965-8

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