COMMUNICATION SYSTEMS, NETWORKS AND DIGITAL SIGNAL PROCESSING Nonlinear complex behaviour of TCP in UMTS networks and performance analysis

Nonlinear dynamic behaviour of transmission control protocol (TCP) in universal mobile telecommunications system (UMTS) networks is proposed. The dynamic characteristics of TCP are explored using the fundamentals of chaos theory, and the occurrence of chaotic beha- viour in relation to the feedback that is received (packet drops, packet delays) by TCP from the network is explained theoritically. To validate the concept proposed, a model of the UMTS network is built and simulated under various user traffic loads. Using standard chaos methodology, it was found that inside the UMTS the TCP exhibits aperiodicity and sensitivity to initial conditions that are inherent characteristics of chaos. In particular, simulation results illustrate that as the traffic load increases, the behaviour of the network ranges from periodically stable to chaotic, with a direct impact on the quality of service of the network.

[1]  Bernhard Walke,et al.  Mobile Radio Networks , 1999 .

[2]  J. Yorke,et al.  Chaos: An Introduction to Dynamical Systems , 1997 .

[3]  Hiroshi Inamura,et al.  TCP over Second (2.5G) and Third (3G) Generation Wireless Networks , 2003, RFC.

[4]  Andras Veres,et al.  The chaotic nature of TCP congestion control , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[5]  Vishal Misra,et al.  Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED , 2000, SIGCOMM 2000.

[6]  Marco Ajmone Marsan,et al.  Using partial differential equations to model TCP mice and elephants in large IP networks , 2004, IEEE INFOCOM 2004.

[7]  Joan García-Haro,et al.  Optimizing TCP and RLC interaction in the UMTS radio access network , 2006, IEEE Network.

[8]  João Pedro Hespanha,et al.  A hybrid systems modeling framework for fast and accurate simulation of data communication networks , 2003, SIGMETRICS '03.

[9]  Donald F. Towsley,et al.  Modeling TCP Reno performance: a simple model and its empirical validation , 2000, TNET.

[10]  François Baccelli,et al.  Flow level simulation of large IP networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[11]  R. Carrasco,et al.  Complex Behaviour in Nonlinear Systems , 1996 .

[12]  Sally Floyd,et al.  Modeling wireless links for transport protocols , 2004, CCRV.

[13]  T. V. Lakshman,et al.  The performance of TCP/IP for networks with high bandwidth-delay products and random loss , 1997, TNET.

[14]  Joel Cartwright,et al.  Practical experience with TCP over GPRS , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[15]  Rolando Carrasco,et al.  Neural networks for the adaptive control of disruptive nonlinear network traffic , 2000 .

[16]  Panganamala Ramana Kumar,et al.  A counterexample in congestion control of wireless networks , 2007, Perform. Evaluation.

[17]  Fei Hu,et al.  The quantitative analysis of TCP congestion control algorithm in third-generation cellular networks based on FSMC loss model and its performance enhancement , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.