IAENG Transactions on Engineering Technologies pp 537-549 | Cite as
Solving VoIP QoS and Scalability Issues in Backbone Networks
Abstract
Providing quality of service should be one of the main objectives when deploying sensitive applications into the network. Since network performance parameters are subject to frequent change, in this chapter we propose a novel approach to routing sensitive VoIP traffic in large networks. Our approach takes measured delay and jitter into consideration and we establish an overlay of the original network to route primarily VoIP traffic. This is achieved by first modeling the probability distributions of network performance parameters and then by calculating the best paths by means of graph algorithm utilizing aspects. Our approach also identifies weak network areas not suitable for VoIP deployment which can be subject to future network improvements.
Keywords
Active measurement Algorithm Delay Jitter Network QoS Routing VoIPNotes
Acknowledgments
The support by Slovak Science Grant Agency (VEGA1/0676/12 “Network architectures for multimedia services delivery with QoS guarantee”) is gratefully acknowledged.
References
- 1.Gunnar A, Johansson A, Telkamp T (2004) Traffic matrix estimation on a large IP backbone: a comparison on real data. In: Proceedings of the 4th ACM SIGCOMM conference on Internet measurement (IMC ’04), pp 149–160, 25–27 Oct 2004Google Scholar
- 2.Lan K-C, Wu T-H (2011) Evaluating the perceived quality of infrastructure-less VoIP. In: IEEE international conference on multimedia and Expo (ICME), 2011, pp 1–6, 11–15 July 2011Google Scholar
- 3.Fortz B, Rexford J, Thorup M (2002) Traffic engineering with traditional IP routing protocols. In: IEEE communications magazine, vol 40, pp 118–124, Dec 2002Google Scholar
- 4.Wang X, Wan S, Li L (2009) Robust traffic engineering using multi-topology routing. In: Global telecommunications conference, 2009, pp 1–6Google Scholar
- 5.Hansen TJ, Morup M, Hansen LK (2011) Non-parametric co-clustering of large scale sparse bipartite networks on the GPU. In: IEEE international workshop on machine learning for signal processing (MLSP), 2011, pp 1–6, 18–21 Sept 2011Google Scholar
- 6.Wang H (2010) From a mess to graphic maps: visualization of large-scale heterogeneous networks. In: Second international conference on, computer modeling and simulation, 2010, ICCMS ’10, vol 1, pp 531–535, 22–24 Jan 2010Google Scholar
- 7.Abrahamsson H, Bjorkman M (2009) Robust traffic engineering using l-balanced weight-settings in OSPF/IS-IS. In: Broadband communications, networks, and systems (BROADNETS), 2009, pp 1–8Google Scholar
- 8.Son H, Lee Y (2010) Detecting anomaly traffic using flow data in the real VoIP network. In: 10th IEEE/IPSJ international symposium on applications and the internet (SAINT), 2010, pp 253–256, 19–23 July 2010Google Scholar
- 9.Tebaldi C, West M (1998) Bayesian inference on network traffic using link count data. J Am Stat Assoc 93(442):557–576. ISSN 0162–1459Google Scholar
- 10.Cao J, Davis D, Vander Wiel S, Yu B (2000) Time-varying network tomography: router link data. J Am Stat 95:1063–1075Google Scholar
- 11.Goldschmidt O (2000) ISP backbone traffic inference methods to support traffic engineering. In: Internet statistics and metrics analysis, workshop (ISMA’00), 7–8 Dec 2000Google Scholar
- 12.Casas P, Vaton S, Fillatre L, Chonavel L (2009) Efficient methods for traffic matrix modeling and on-line estimation in large-scale IP networks. In: Proceedings of 21st international teletraffic congress, 2009. ITC 21 2009, pp 1–8, 15–17 Sept 2009Google Scholar
- 13.Liu B, Choo S-H, Lok S-L, Leong S-M, Lee S-C, Poon F-P, Tan H-H (1994) Finding the shortest route using cases, knowledge, and Djikstra’s algorithm. IEEE Expert 9(5):7–11Google Scholar
- 14.Noto M, Sato H (2000) A method for the shortest path search by extended Dijkstra algorithm. In: IEEE international conference on systems, man, and cybernetics, 2000, vol 3, pp 2316–2320Google Scholar
- 15.Guttoski PB, Sunye MS, Silva F (2007) Kruskal’s algorithm for query tree optimization. In: Proceedings of 11th international database engineering and applications symposium, 2007. IDEAS 2007, pp 296–302, 6–8 Sept 2007Google Scholar
- 16.Butcher D, Li X, Guo J (2007) Security challenge and defense in VoIP infrastructures. In: IEEE transactions on systems, man, and cybernetics, part C: applications and reviews vol 37, no 6, pp 1152–1162Google Scholar
- 17.Narayan S, Yhi S (2010) Application layer network performance evaluation of VoIP traffic on a test-bed with IPv4 and IPv6 LAN infrastructure. In: IEEE Region 8 international conference on computational technologies in electrical and electronics engineering (SIBIRCON), 2010, pp 215–219, 11–15 July 2010Google Scholar
- 18.Xiao J, Boutaba R (2005) QoS-aware service composition in large scale multi-domain networks. In: Proceedings of 9th IFIP/IEEE international symposium on integrated network management, 2005. IM, pp 397–410, 15–19 May 2005Google Scholar
- 19.Okech JM, Hamam Y, Kurien A (2008) A cross-layer adaptation for VoIP over infrastructure mesh network. In: Third international conference on proceedings of broadband communications. Information Technology & Biomedical Applications, Nov, pp 97–102Google Scholar
- 20.Cao F, Malik S (2006) Vulnerability analysis and best practices for adopting IP telephony in critical infrastructure sectors. IEEE Commun Mag 44(4):138–145Google Scholar
- 21.Hruby M, Olsovsky M, Kotocova M (2012) Routing VoIP traffic in large networks. Lecture notes in engineering and computer science: proceedings of the world congress on engineering (2012) WCE 2012, London, UK, pp 798–803, 4–6 July 2012Google Scholar