CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Simulation Design and Performance Analysis for VoIP in Cognitive Radio Networks

by Tamal Chakraborty, Iti Saha Misra, Salil Kumar Sanyal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 5
Year of Publication: 2013
Authors: Tamal Chakraborty, Iti Saha Misra, Salil Kumar Sanyal
10.5120/10076-4688

Tamal Chakraborty, Iti Saha Misra, Salil Kumar Sanyal . Simulation Design and Performance Analysis for VoIP in Cognitive Radio Networks. International Journal of Computer Applications. 62, 5 ( January 2013), 15-23. DOI=10.5120/10076-4688

@article{ 10.5120/10076-4688,
author = { Tamal Chakraborty, Iti Saha Misra, Salil Kumar Sanyal },
title = { Simulation Design and Performance Analysis for VoIP in Cognitive Radio Networks },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 5 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 15-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number5/10076-4688/ },
doi = { 10.5120/10076-4688 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:10:53.866907+05:30
%A Tamal Chakraborty
%A Iti Saha Misra
%A Salil Kumar Sanyal
%T Simulation Design and Performance Analysis for VoIP in Cognitive Radio Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 5
%P 15-23
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Increasing popularity of VoIP systems has witnessed applications in emerging technologies like Cognitive Radio Networks (CRN). The stringent QoS requirements in VoIP coupled with complexities in CRN have initiated intensive research in the field of performance analysis and optimizations guided by simulation results. However, in the absence of any standard model of VoIP over CRN, accuracy and credibility of the simulation output are strongly dependent on proper design of the simulation model that must have a strong mathematical foundation. The objective of this paper is to build standard models for VoIP in CRN and successfully implement VoIP applications over CRN domain, which will serve as initial point for development with respect to all future simulation studies in VoIP over CRN category. Initially, models of VoIP in CRN are developed using OPNET Modeler 16. 0. A following distributed architecture in single-channel and multi-channel scenarios and further in Visual C++ adhering to the principles of centralized architecture. The models are validated by comparison of simulation results obtained in both platforms. The underlying mathematical model behind the design is established and the critical factors pertaining to both VoIP and CRN domain are extensively analyzed.

References
  1. Federal Communications Commission. Notice of proposed rule making and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies. ET Docket No. 03-108. 2005.
  2. Y'ucek, T. and Arslan, H. First Quarter 2009. A survey of spectrum sensing algorithms for cognitive radio applications. In Proceedings of IEEE Communications Surveys and Tutorials. vol. 11. no. 1. pp. 116–130. doi= 10. 1109/SURV. 2009. 090109.
  3. Mitola III, J. and Maguire, Jr G. Q. Aug. 1999. Cognitive radio: making software radios more personal. In Proceedings of IEEE Personal Communications. vol. 6. no. 4. pp. 13–18. doi= 10. 1109/98. 788210.
  4. Khasnabish, B. 2003. Implementing Voice over IP. Wiley-Interscience. John Wiley & Sons, Inc.
  5. Lee, H. and Cho, D. June 2009. VoIP Capacity Analysis in Cognitive Radio System. In Proceedings of IEEE Communication Letters. vol. 13. no. 6. pp. 393-395. doi= 10. 1109/LCOMM. 2009. 082189.
  6. Lee, H. and Cho, D. May 2010. Capacity Improvement and Analysis of VoIP Service in a Cognitive Radio System. IEEE Transactions on Vehicular Technology. vol. 59. no. 4. pp. 1646-1651. doi= 10. 1109/TVT. 2009. 2039503.
  7. Jiang, L. , Jiang, T. , Wang, Z. and He, X. 23-25, September 2010. VoIP Capacity Analysis in Cognitive Radio System with Single/Multiple Channels. In Proceedings of 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM). pp. 1-4. doi= 10. 1109/WICOM. 2010. 5600795.
  8. Zhongliang, L. , Shan, F. , Dongmei, Z. and Shen, X. S. January 2011. Delay Performance Analysis for Supporting Real-Time Traffic in a Cognitive Radio Sensor Network. IEEE Transactions on Wireless Communications. vol. 10. no. 1. pp. 325-335. doi= 10. 1109/TWC. 2010. 111910. 100804.
  9. Mitola III, J. November 1999. Cognitive radio for flexible mobile multimedia communication. In Proceedings of IEEE International Workshop on Mobile Multimedia Communications (MoMuC). pp. 3–10. doi= 10. 1109/MOMUC. 1999. 819467.
  10. Li, J. , Xu, B. , Xu, Z. , Li, S. , and Liu, Y. 2006. Adaptive packet scheduling algorithm for cognitive radio system. In Proceedings of ICCT. pp. 1–5.
  11. Pawlikowski, K. , Jeong, H. -D. J. , Lee, J. -S. R. Jan 2002. On credibility of simulation studies of telecommunication networks. In Proceedings of IEEE Communications Magazine. vol. 40. no. 1. pp. 132-139. doi= 10. 1109/35. 978060.
  12. Sargent, R. J. 5-8 Dec. 2010. Advanced tutorial: Overview of simulation world views. In Proceedings of the 37th Conference on Winter Simulation (WSC). pp. 210-215. doi= 10. 1109/WSC. 2010. 5679161.
  13. Hevner, A. R. , March, S. T. , Park, J and Ram, S. 2004. Design research in information systems research. MIS Quarterly, vol. 28. Issue 1. pp. 75–105.
  14. Rao, D. M. and Wilsey, P. A. 2001. Modeling and simulation of active networks. In 34th Annual Proceedings of Simulation Symposium. pp. 177-184. doi= 10. 1109/SIMSYM. 2001. 922130.
  15. ITU-T. 1972. G. 711: Pulse Code Modulation (PCM) of Voice Frequencies.
  16. O. Inc, "OPNET Modeler. " [Online]. Available: http://www. opnet. com.
  17. Akyildiz, I. F. , Lee, W. Y. , Vuran, M. C. , and Mohanty, S. Sept. 2006. NeXt generation/dynamic spectrum access / cognitive radio wireless networks: A survey. Computer Networks Journal (Elsevier) 50. pp. 2127- 2159.
  18. Wang, P. , Xiao, L. , Zhou, S. , and Wang, J. 11-15 March 2007. Optimization of detection time for channel efficiency in cognitive radio systems. In Proceedings of IEEE Wireless Communication and Networking Conference. pp. 111–115. Hong Kong. doi= 10. 1109/WCNC. 2007. 26.
  19. Cabric, D. , Mishra, S. M. , and Brodersen, R. W. 7-10 Nov. 2004. Implementation issues in spectrum sensing for cognitive radios. In Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers. pp. 772- 776. vol. 1. doi= 10. 1109/ACSSC. 2004. 1399240.
  20. Mall, R. 2011. Fundamentals of Software Engineering. PHI Learning Private Limited. 3rd ed.
  21. Pegden, C. D. 5-8 Dec. 2010. Advanced tutorial: Overview of simulation world views. In Proceedings of the 2010 Winter Simulation Conference (WSC). pp. 210-215. doi= 10. 1109/WSC. 2010. 5679161.
  22. Soliman, H. M. , Elmaghraby, A. S. and El-Sharkawy, M. A. 27-29 July 1995. Parallel and distributed simulation: an overview. In Proceedings of IEEE Symposium on Computers and Communications. pp. 270-276. doi= 10. 1109/SCAC. 1995. 523677.
  23. Balci, O. , Nance, R. E. , Derrick, E. J. , Page, E. H. and Bishop, J. L. 9-12 Dec 1990. Model generation issues in a simulation support environment. In Proceedings of Winter Simulation Conference. pp. 257-263. doi= 10. 1109/WSC. 1990. 129524.
  24. Visual C++ Programmer's Guide. Available: http://msdn. microsoft. com/enus/library/.
  25. Shinn, T. 2006. When is Simulation a Research-Technology? Practices, Markets and Lingua Franca. In Proceedings of Simulation, Sociology of the Sciences Yearbook. vol. 25. part 4. pp. 187-203. doi= 10. 1007/1-4020-5375-4_12.
  26. Bratley P. Fox B. L. and Schrage L. E. 1987. A guide to simulation, 2nd ed. Springer.
  27. Robinson, S. 11-14 Dec. 2011. Choosing the right model: Conceptual modeling for simulation. In Proceedings of the 2011 Winter Simulation Conference (WSC). pp. 1423-1435. doi= 10. 1109/WSC. 2011. 6147862.
  28. Fritzson, P. 2004. Principles of Object-Oriented Modeling and Simulation with Modelica 2. 1. Wiley-IEEE Press.
  29. Merkuryeva, G. and Vecherinska, O. 24-26 March 2010. Simulation-Based Comparison: An Overview and Case Study. In Proceedings of 12th International Conference on Computer Modelling and Simulation (UKSim). pp. 186-190.
  30. Wang, L. , Wang, C. and Chang, C. Sept. 2012. Modeling and Analysis for Spectrum Handoffs in Cognitive Radio Networks. IEEE Transactions on Mobile Computing. vol. 11. no. 9. pp. 1499-1513. doi= 10. 1109/TMC. 2011. 155.
  31. Qaimkhani, I. A. and Hossain, E. January 2008. Efficient silence suppression and call admission control through contention-free medium access for VoIP in WiFi networks. IEEE Communications Magazine. vol. 46. no. 1. pp. 90-99. doi= 10. 1109/MCOM. 2008. 4427236.
  32. Lai, L. J. , Ren, L. P. , Dutkiewicz, E. and Vesilo, R. 15-18 May 2011. Optimal Channel Reservation in Cooperative Cognitive Radio Networks. In Proceedings of 73rd IEEE Vehicular Technology Conference (VTC Spring). pp. 1-6. doi= 10. 1109/VETECS. 2011. 5956171.
  33. Forgie, J. W. 19-22 May, 1975. Speech transmission in packet-switched store and-forward networks. In Proceedings of AFIPS '75. pp. 137-142. doi= 10. 1145/1499949. 1499978.
Index Terms

Computer Science
Information Sciences

Keywords

Voice Over IP Cognitive Radio Network Simulation OPNET Modeler 16. 0. A. Visual C++

Powered by PhDFocusTM