Statistical multiplexing strategies for self-similar traffic

Traffic-shifting and shuffle methods are proposed as statistical multiplexing strategies for self-similar traffic sources. The purpose of these strategies is to decrease the burstiness of the traffic. This paper explores the Hurst parameter, and autocorrelation of the homogenous and heterogenous traffic. The simulation initially investigates the traffic with and without strategies implementation. Finally the comparisons between both methods are explored. The simulation results show that the strategies can decline the burstiness of the traffic. When contrasting the traffic performances achieved by both strategies, no large differences of H-parameters and autocorrelation coefficients of the traffic are observed.

[1]  Walter Willinger,et al.  Experimental queueing analysis with long-range dependent packet traffic , 1996, TNET.

[2]  Stefano Giordano,et al.  Statistical multiplexing of self-similar VBR videoconferencing traffic , 1997, GLOBECOM 97. IEEE Global Telecommunications Conference. Conference Record.

[3]  H. Mehrpour,et al.  Self-similar traffic generator: comparison between RMD and SRA methods , 2002, 5th IEEE International Conference on High Speed Networks and Multimedia Communication (Cat. No.02EX612).

[4]  Jin Cao,et al.  The Effect of Statistical Multiplexing on the Long-Range Dependence of Internet Packet Traffic , 2001 .

[5]  Jianjun Shi,et al.  Merging and splitting self-similar traffic , 1999, Fifth Asia-Pacific Conference on ... and Fourth Optoelectronics and Communications Conference on Communications,.

[6]  Carey L. Williamson,et al.  Statistical multiplexing of self-similar video streams: simulation study and performance results , 1998, Proceedings. Sixth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (Cat. No.98TB100247).

[7]  I Made Suartika,et al.  SELF-SIMILAR TRAFFIC GENERATOR , 2005 .

[8]  Ilkka Nomos.  On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks , 1995 .

[9]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1999, TNET.

[10]  Nelson Luis Saldanha da Fonseca,et al.  Statistical multiplexing of self-similar sources , 2000, Globecom '00 - IEEE. Global Telecommunications Conference. Conference Record (Cat. No.00CH37137).

[11]  Ilkka Norros,et al.  A storage model with self-similar input , 1994, Queueing Syst. Theory Appl..

[12]  Nelson L. S. da Fonseca,et al.  Policing and statistical multiplexing of self-similar sources , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[13]  Parag Pruthi,et al.  An application of deterministic chaotic maps to model packet traffic , 1995, Queueing Syst. Theory Appl..

[14]  Jian Gui-zhou.  Statistical Multiplexing of Self-similar Traffic , 2002 .

[15]  José Augusto Suruagy Monteiro,et al.  Statistical multiplexing of aggregate data traffic in ATM networks , 1998, ITS'98 Proceedings. SBT/IEEE International Telecommunications Symposium (Cat. No.98EX202).

[16]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1996, SIGCOMM 1996.