KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Clustering-Based Mobile Gateway Management in Integrated CRAHN-Cloud Network

  • Hou, Ling (School of Science and Technology, The Open University of Hong Kong) ;
  • Wong, Angus K.Y. (School of Science and Technology, The Open University of Hong Kong) ;
  • Yeung, Alan K.H. (Department of Electronic Engineering, City University of Hong Kong) ;
  • Choy, Steven S.O. (School of Science and Technology, The Open University of Hong Kong)
  • Received : 2017.05.07
  • Accepted : 2018.02.05
  • Published : 2018.07.31
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Abstract

The limited storage and computing capacity hinder the development of cognitive radio ad hoc networks (CRAHNs). To solve the problem, a new paradigm of cloud-based CRAHN has been proposed, in which a CRAHN will make use of the computation and storage resources of the cloud. This paper envisions an integrated CRAHN-cloud network architecture. In this architecture, some cognitive radio users (CUs) who satisfy the required metrics could perform as mobile gateway candidates to connect other ordinary CUs with the cloud. These mobile gateway candidates are dynamically clustered according to different related metrics. Cluster head and time-to-live value are determined in each cluster. In this paper, the gateway advertisement and discovery issues are first addressed to propose a hybrid gateway discovery mechanism. After that, a QoS-based gateway selection algorithm is proposed for each CU to select the optimal gateway. Simulations are carried out to evaluate the performance of the overall scheme, which incorporates the proposed clustering and gateway selection algorithms. The results show that the proposed scheme can achieve about 11% higher average throughput, 10% lower end-to-end delay, and 8% lower packet drop fractions compared with the existing scheme.

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References

  1. J. Mitola and G. Maguire, "Cognitive radio: making software radios more personal," IEEE Personal Communications, Vol. 6, No. 4, pp. 13-18, 1999. https://doi.org/10.1109/98.788210
  2. S. Haykin, "Cognitive radio: Brain-empowered wireless communications," IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201-220, Feb. 2005. https://doi.org/10.1109/JSAC.2004.839380
  3. Ian F. Akyildiz, W. Lee, M. Vuran, and S. Mohanty, "NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey," Computer Networks, vol. 50, no. 13, pp. 2127-2159, 2006. https://doi.org/10.1016/j.comnet.2006.05.001
  4. Elias Z. Tragos, Sherali Zeadally, Alexandros G. Fragkiadakis and Vasilios A. Siris, "Spectrum Assignment in Cognitive Radio Networks: A Comprehensive Survey," IEEE Communications Surveys & Tutorials, Vol. 15, Iss. 3, pp. 1108-1135, 2013. https://doi.org/10.1109/SURV.2012.121112.00047
  5. N. Devroye, M. Vu, and V. Tarokh, "Cognitive radio networks," IEEE Signal Process. Mag., vol. 25, no. 6, pp. 12-23, Nov. 2008. https://doi.org/10.1109/MSP.2008.929286
  6. I. F. Akyildiz, W. Y. Lee, and K. R. Chowdhury, "CRAHNs: Cognitive radio ad hoc networks," Ad Hoc Networks Elsevier, 7(5), pp. 810-836, 2009. https://doi.org/10.1016/j.adhoc.2009.01.001
  7. Kamal Deep Singh, Priyanka Rawat and Jean-Marie Bonnin, "Cognitive radio for vehicular ad hoc networks (CR-VANETs): approaches and challenges," EURASIP Journal on Wireless Communications and Networking, no. 49, 2014.
  8. R. Yu, Y. Zhang, S. Gjessing, W. Xia, K. Yang, "Toward Cloud-Based Vehicular Networks with Efficient Resource Management," IEEE Network, vol. 27, no. 5, pp. 48-55, Sep 2013. https://doi.org/10.1109/MNET.2013.6616115
  9. Feng Ge, Heshan Lin, Amin Khajeh, C. Jason Chiang, Ahmed M. Eltawil, Charles W. Bostian, Wu-chun Feng, and Ritu Chadha, "Cognitive radio rides on the cloud," in Proc. of Military Communications Conference (MILCOM), pp.1448-1453, 2011.
  10. Y. B Reddy and S. Ellis, "Modeling Cognitive Radio Networks for Efficient Data Transfer Using Cloud Link," in Proc. of Tenth International Conference on Information Technology: New Generations (ITNG), pp. 525-530, 2013.
  11. C.H. Ko, D.H. T. Huang and S.H. Wu, "Cooperative Spectrum Sensing in TV White Spaces: When Cognitive Radio Meets Cloud," in Proc. of IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp.672-677, 2011.
  12. Sau-Hsuan Wu, Hsi-Lu Chao, Chun-Hsien Ko, Shang-Ru Mo, et al, "A Cloud Model and Concept Prototype for Cognitive Radio Networks," IEEE Wireless Communications, vol.19, iss.4, pp. 49-58, 2012. https://doi.org/10.1109/MWC.2012.6272423
  13. N. Cordeshi, D. Amendola, and E. Baccarelli, "Reliable adaptive resource management for cognitive cloud vehicular networks," IEEE Transactions on Vehicular Technology, vol. 64, no. 6, pp. 2528-2537, Jun. 2015. https://doi.org/10.1109/TVT.2014.2345767
  14. H.T. Dinh, C. Lee, D. Niyato, and P. Wang, "A survey of mobile cloud computing: architecture, applications, and approaches," Wireless Communications and Mobile Computing, 2011.
  15. P. Thanapal, A. Varshney, and M. A. Saleem Durai, "A Survey on Cloud Computing for Mobile Users: Making Smartphones Last Longer with Computation Offload," International Journal of Computer Applications, vol. 56, no.18, 2012.
  16. Pablo Punal Pereira, Jens Eliasson, Rumen Kyusakov, Jerker Delsing, Asma Raayatinezhad, and Mia Johansson, "Enabling Cloud Connectivity for Mobile Internet of Things Applications," in Proc. of IEEE Seventh International Symposium on Service-Oriented System Engineering (SOSE'13), pp. 518-526, 2013.
  17. M. Jo, T. Maksymyuk, B. Strykhalyuk, and C.-H. Cho, "Deviceto-device-based heterogeneous radio access network architecture for mobile cloud computing," IEEE Wireless Commun., vol. 22, no. 3, pp. 50-58, Mar. 2015. https://doi.org/10.1109/MWC.2015.7143326
  18. Vinod Namboodiri, Manish Agarwal , and Lixin Gao, "A study on the feasibility of mobile gateways for vehicular ad-hoc networks," in Proc. of Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks, October 01-01, 2004, Philadelphia, PA, USA.
  19. A. Benslimane, T. Taleb, R. Sivaraj, "Dynamic Clustering-Based Adaptive Mobile Gateway Management in Integrated VANET C 3G Heterogeneous Wireless Networks," IEEE Journal on Selected Areas in Communication, vol. 29, no. 3, pp. 559-570, March 2011. https://doi.org/10.1109/JSAC.2011.110306
  20. P. Angove, M. O'Grady, J. Hayes, B. O'Flynn, G. M. P. O'Hare, and D. Diamond, "A Mobile Gateway for Remote Interaction With Wireless Sensor Networks," Sensors Journal IEEE, pp. 3309-3310, Dec. 2011.
  21. H. Ammari, and H. El-Rewini, "Integration of Mobile Ad Hoc Networks and the Internet Using Mobile Gateways," in Proc. of Proceedings of the 18th International Parallel and Distributed Processing Symposium, pp. 218-225, April 2004.
  22. T. Chen, H. Zhang, G. M. Maggio, and I. Chlamtac, "CogMesh: A cluster-based cognitive radio network," in Proc. of 2nd IEEE International Symposium on New Frontier in Dynamic Spectrum Access Networks, pp. 168-178, 2007.
  23. C. Sun, W. Zhang, and K. Ben, "Cluster-based cooperative spectrum sensing in cognitive radio systems," in Proc. of IEEE International Conference on Communications (ICC'07), pp. 2511-2515, Jun. 2007.
  24. S. Liu, L. Lazos, and M. Krunz, "Cluster-Based Control Channel Allocation in Opportunistic Cognitive Radio Networks," IEEE Transactions on Mobile Computing, vol. 11, no. 10, pp. 1436-1449, 2012. https://doi.org/10.1109/TMC.2012.33
  25. H. Zhang, Z. Zhang, H. Dai, R. Yin, and X. Chen, "Distributed spectrum-aware clustering in cognitive radio sensor networks," in Proc. of Global Telecommunications Conference (GLOBECOM 2011), pp. 1-6, 2011.
  26. D. Li and J. Gross, "Robust clustering of ad-hoc cognitive radio networks under opportunistic spectrum access," in Proc. of IEEE International Conference on Communications (ICC 2011), pp. 1-6, 2011.
  27. L. Lazos, S. Liu, and M. Krunz, "Spectrum opportunity-based control channel assignment in cognitive radio networks," in Proc. of 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON'09), pp. 1-9, 2009.
  28. Zhiyong Lin, Hai Liu, Xiaowen Chu, Yiu-Wing Leung and Ivan Stojmenovic, "Constructing Connected-Dominating-Set with Maximum Lifetime in Cognitive Radio Networks," IEEE Transactions on Computers, vol. pp, iss. 99, 2013.
  29. Y. Bai, and L. Gong, "Link availability prediction with radio irregularity coverage for mobile multi-hop networks," IEEE Communications Letters, vol. 14, no. 6, pp. 518-520, 2010. https://doi.org/10.1109/LCOMM.2010.06.100238
  30. S. Jiang, "An enhanced prediction-based link availability estimation for MANETs," IEEE Transactions on Communications, vol. 52, no. 2, pp. 183-186, Feb. 2004. https://doi.org/10.1109/TCOMM.2003.822739
  31. Q. Guan, F. R. Yu, S. Jiang and G. Wei, "Prediction-based topology control and routing in cognitive radio mobile ad hoc networks," IEEE Transactions on Vehicular Technology, vol. 59, no. 9, pp.4443-4452, 2010. https://doi.org/10.1109/TVT.2010.2069105
  32. N. ul Hasan, W. Ejaz, K. Manzoor, and H. S. Kim, "GSM: gateway selection mechanism for strengthening inter-cluster coordination in cognitive radio ad hoc networks," EURASIP Journal on Wireless Communications and Networking, vol. 2013, no. 1, pp. 1-11, Jun. 2013. https://doi.org/10.1186/1687-1499-2013-1
  33. G. Zhioua, H. Labiod, N. Tabbane, S. Tabbane, "FQGwS: A Gateway Selection Algorithm in a Hybrid Clustered VANET LTE-Advanced Network: Complexity and Performances," in Proc. of Proceeding of 2014 International Conference on Computing Networking and Communications (ICNC), pp. 413-417, 2014.