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Intelligent multicast routing for multimedia over cognitive radio networks: a probabilistic approach

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Abstract

Cognitive radio (CR) technology has been demonstrated as one of the key technologies that can provide the needed spectrum bands for supporting the emerging spectrum-hungry multimedia applications and services in next-generation wireless networks. Multicast routing technique plays a significant role in most of wireless networks that require multimedia data dissemination to a group of destinations through single-hop or multi-hop communication. Performing multimedia multicasting over CR networks can significantly improve the quality of multimedia transmissions by effectively exploiting the available spectrum, reducing network traffic and minimizing communication cost. An important challenge in this domain is how to perform a multi-cast transmissions over multiple hops in a dynamically varying CR environment while maintaining high-quality received video streaming to all multi-case CR receivers without affecting the performance of legacy primary radio networks (PRNs). In this paper, we investigate the problem of multicast multimedia streaming in multi-hop CR networks (CRNs). Specifically, we propose an intelligent multicast routing protocol for multi-hop ad hoc CRNs that can effectively support multimedia streaming. The proposed protocol consists of path selection and channel assignment phases for the different multi-cast receivers. It is based on the shortest path tree (SPT) that implements the expected transmission count metric (ETX). The channel selection is based on the ETX, which is a function of the probability of success (POS) over the different channels that depends on the channel-quality and availability. Simulation results verify the significant improvement achieved by the proposed protocol compared to other existing multicast routing protocols under different network conditions.

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References

  1. Al-hammouri M, et al. (2018) Scalable video streaming for real-time multimedia applications over dds middleware for future internet architecture." 2018 IEEE/ACS 15th International Conference on computer Systems and Applications (AICCSA)

  2. S. Almajali, D. Abou-Tair, et. al., “A distributed multi-layer MEC-cloud architecture for processing large scale IoT-based multimedia applications", Multimed Tools Appl, vol. 78, no. 17, pp. 24617–24638, 2019.

  3. Almasaeid HM, Jawadwala TH, and Kamal AE (2010) “On-Demand multicast routing in cognitive radio mesh networks” , Global Telecommunications Conference, Global Communications, pp. 1–5, Miami, FL, 6–10

  4. M. Aloqaily, I. A. Ridhawi, et. al., “Data and Service Management in Densely Crowded Environments: challenges, opportunities, and recent developments," in IEEE Commun Mag, vol. 57, no. 4, pp. 81–87, 2019.

  5. Al-rubaye M, Bany Salameh H, Jararweh Y (2016) " Minimum spanning tree-based multicast routing protocol for dynamic spectrum access networks: A multi-layer probabilistic approach," the 7th IEEE International Conference on computer Science and Information Technology (CSIT)

  6. Amjad M, Rehmani MH, Mao S (2018) Wireless multimedia cognitive radio networks: a comprehensive survey. in IEEE Communications Surveys & Tutorials 20(2):1056–1103

    Article  Google Scholar 

  7. Balakrishnan VK (1997) “Schaum’s outline of theory and problems of graph theory”, McGraw-Hill

  8. Bany Salameh H, El-Attar M (2015) Cooperative OFDM-based virtual clustering scheme for distributed coordination in cognitive radio networks. IEEE Trans Veh Technol 64(8):3624–3632

    Article  Google Scholar 

  9. Bany Salameh H, Krunz M and Younis O (2009) "Dynamic Spectrum Access Protocol Without Power Mask Constraints," IEEE INFOCOM 2009, Rio de Janeiro, pp. 2322–2330

  10. Bany Salameh H, Almajali S, Ayyash M, Elgala H (2018) Spectrum assignment in cognitive radio networks for internet-of-things delay-sensitive applications under jamming attacks. IEEE Internet Things J 5:1904–1913

    Article  Google Scholar 

  11. Bany Salameh H, Otoum S, et al (2019) Intelligent jamming-aware routing in multi-hop IoT-based opportunistic cognitive radio networks, Ad Hoc Netw

  12. Bdarneh O and Bany Salameh H (2011) “Opportunistic routing in cognitive radio network: exploiting availability and rich channel diversity", IEEE GlobeCom, pp. 1–5, Houston, TX, USA, 5–9

  13. Cheng G, Liu W, Li Y, and Cheng W (2007) “Joint on-demand routing and spectrum assignment in cognitive radio networks,” Proceedings of IEEE International Conference on Communications (ICC), pp. 6499-6503

  14. Couto D, Aguayo D, Bicket J, Morris R (2003) “A high-throughput path metric for multi-hop wireless routing,” in Proceedings of the Ninth Annual International Conference on Mobile Computing and Networking, MOBICOM 2003, SanDiego, CA, USA, pp. 134–146.

  15. Elhassan M, Abd-Elnaby M, et. al (2019) "Throughput maximization for multimedia communication with cooperative cognitive radio using adaptively controlled sensing time", Multimed Tools Appl

  16. Ge Y, Chen M, Sun Y et al (2013) “QoS provisioning wireless multimedia transmission over cognitive radio networks, “ Multimed Tools Appl, pp. 67–213

  17. Hu D, Mao S, and Reed JH “On video multicast in cognitive radio networks” , IEEE INFOCOM, pp. 2222–2230, Rio de Janeiro, 19–25 April 2009

  18. Jararweh Y, Al Ayyoub M, et. al (2014) “SD-CRN: Software defined cognitive radio network framework," In 2014 IEEE International Conference on Cloud Engineering, pp. 592–597

  19. Khan A, Rehmani MH, Rachedi A (2017) Cognitive-radio-based internet of things: Applications, architectures, spectrum related functionalities, and future research directions. IEEE Wireless Communications 23:17–25

    Article  Google Scholar 

  20. Lee S, Gerla M and Chiang C (1999) “On-Demand multicast routing protocol”, Proceedings of the IEEE wireless communications and networking conference, pp. 1 298–302, New Orleans, USA

  21. Lin T, Yang G, Kwong WC (April 2019) A homogeneous multi-radio rendezvous algorithm for cognitive radio networks. in IEEE Communications Letters 23(4):736–739

    Article  Google Scholar 

  22. Maity SP (2017) "Joint power allocation and route selection for outage minimization in multi-hop cognitive radio networks with energy harvesting," IEEE Transactions on Cognitive Communications and Networking , PP. 82–92, Vol. 4

  23. Mhaidat Y, Alsmirat M, Badarneh OS, et al (2014) A cross-layer video multicasting routing protocol for cognitive radio networks, 2014 IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Larnaca, pp. 384-389

  24. Mhaidat Y, et al (2014) “A Cross-Layer video multicasting routing protocol for cognitive radio networks”, the seventh international workshop on selected topics in mobile and wireless computing

  25. Nguyen H, Nguyen UT (2009) Channel assignment for multicast in multi-channel multi-radio wireless mesh networks. Wireless Communications and Mobile Computing 9(4):557–571

    Article  Google Scholar 

  26. Rabsatt T, Gerla V (2014) “Cognitive routing with the ETX metric,” Ad Hoc Networking Workshop (MED-HOC-NET), pp.188–194

  27. Saniya Z et al (2019) QoS enhancement with deep learning-based interference prediction in mobile Io. Computer Communications 148:86–97

    Article  Google Scholar 

  28. Shah MA, Zhang S, Maple C (2013) Cognitive radio networks for internet of things: Applications, challenges and future, in: 2013 19th International Conference on Automation and Computing, pp. 1–6

  29. Ye Wu B and Chao K (2004) “Spanning trees and optimization problems”, CRC Press

  30. Zeng G, Wang B, Ding Y, Xiao L, and Mutka M (2007) “Multicast algorithms for multi-channel wireless mesh networks”, IEEE International Conference on Network Protocols (ICNP), pp. 1–10, Beijing, 16–19

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Authors and Affiliations

  1. Network and Communications Engineering Department, Al Ain University, Al Ain, United Arab Emirates

    Haythem Bany Salameh

  2. Telecommunications Engineering Department, Yarmouk University, Irbid, Jordan

    Haythem Bany Salameh & Rasha Abusamra

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  1. Haythem Bany Salameh
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  2. Rasha Abusamra
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Correspondence to Haythem Bany Salameh.

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Bany Salameh, H., Abusamra, R. Intelligent multicast routing for multimedia over cognitive radio networks: a probabilistic approach. Multimed Tools Appl 80, 16731–16742 (2021). https://doi.org/10.1007/s11042-020-08732-w

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  • DOI: https://doi.org/10.1007/s11042-020-08732-w

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