TY - GEN

T1 - Discrete event simulation with application to computer communication systems performance

T2 - IFIP 18th World Computer Congress, WCC 2004

AU - Szczerbicka, Helena

AU - Trivedi, Kishor S.

AU - Choudhary, Pawan K.

PY - 2004

Y1 - 2004

N2 - As complexity of computer and communication systems increases, it becomes hard to analyze the system via analytic models. Measurement based system evaluation may be too expensive. In this tutorial, discrete event simulation as a model based technique is introduced. This is widely used for the performance/availability assessment of complex stochastic systems. Importance of applying a systematic methodology for building correct, problem dependent, and credible simulation models is discussed. These will be made evident by relevant experiments for different real-life problems and interpreting their results. The tutorial starts providing motivation for using simulation as a methodology for solving problems, different types of simulation (steady state vs. terminating simulation) and pros and cons of analytic versus simulative solution of a model. This also includes different classes of simulation tools existing today. Methods of random deviate generation to drive simulations are discussed. Output analysis, involving statistical concepts like point estimate, interval estimate, confidence interval and methods for generating it, is also covered. Variance reduction and speedup techniques like importance sampling, importance splitting and regenerative simulation are also mentioned. The tutorial discusses some of the most widely used simulation packages like OPNET MODELER and ns-2. Finally the tutorial provides several networking examples covering TCP/IP, FTP and RED.

AB - As complexity of computer and communication systems increases, it becomes hard to analyze the system via analytic models. Measurement based system evaluation may be too expensive. In this tutorial, discrete event simulation as a model based technique is introduced. This is widely used for the performance/availability assessment of complex stochastic systems. Importance of applying a systematic methodology for building correct, problem dependent, and credible simulation models is discussed. These will be made evident by relevant experiments for different real-life problems and interpreting their results. The tutorial starts providing motivation for using simulation as a methodology for solving problems, different types of simulation (steady state vs. terminating simulation) and pros and cons of analytic versus simulative solution of a model. This also includes different classes of simulation tools existing today. Methods of random deviate generation to drive simulations are discussed. Output analysis, involving statistical concepts like point estimate, interval estimate, confidence interval and methods for generating it, is also covered. Variance reduction and speedup techniques like importance sampling, importance splitting and regenerative simulation are also mentioned. The tutorial discusses some of the most widely used simulation packages like OPNET MODELER and ns-2. Finally the tutorial provides several networking examples covering TCP/IP, FTP and RED.

KW - OPNET MODELER and ns-2

KW - Random variate

KW - Simulation

KW - Statistical analysis

KW - TCP/IP

UR - http://www.scopus.com/inward/record.url?scp=84869083914&partnerID=8YFLogxK

U2 - 10.1007/1-4020-8159-6_10

DO - 10.1007/1-4020-8159-6_10

M3 - Conference contribution

AN - SCOPUS:84869083914

SN - 9781402081583

T3 - IFIP Advances in Information and Communication Technology

SP - 271

EP - 304

BT - Information Technology

Y2 - 22 August 2004 through 27 August 2004

ER -