Contributions to Simulation Speed-Up (eBook)

Rare Event Simulation and Short-Term Dynamic Simulation for Mobile Network Planning

Eugen Lamers (Autor)

eBook Download: PDF

2008 | 2008
XXI, 148 Seiten
Vieweg & Teubner (Verlag)
978-3-8348-9513-4 (ISBN)

Infos

Eugen Lamers explains the principle of simulation speed-up in general and shortly demonstrates the technique RESTART for the simulation of rare events. He introduces the Short-Term Dynamic Simulation concept, developed for the planning of mobile radio networks.

Dr. Eugen Lamers works on quality assurance in the field of automation.

Inhalt

Preface 6
Vorwort 7
Abstract 8
Kurzfassung 9
Contents 10
List of Abbreviations 13
List of Symbols 15
List of Figures 18
List of Tables 20
Chapter 1 Introduction 21
Chapter 2 Statistical Accuracy 23
2.1 Discrete event simulation 23
2.2 State space coverage 24
2.3 Parallelisation 34
2.4 Statistical evaluation with LRE 36
Chapter 3 Simulation Speed-up with RESTART 39
3.1 RESTART fundamentals 39
3.2 Importance function 44
3.3 States in single-step 46
3.4 Threshold re.nement 51
Chapter 4 Distributed RESTART 60
4.1 Methodological aspects 60
4.2 Simulations 67
4.3 Conclusions 72
Chapter 5 Short- Term Dynamic Simulation Concept 74
5.1 Classi.cation 74
5.2 Concept 76
5.3 Analytical investigation 79
5.4 Combined speed-up approaches 111
5.5 Conclusions 115
Chapter 6 STD Simulation of UMTS Models 116
6.1 Introduction to UMTS 116
6.2 UMTS simulation concept 118
6.3 Evaluation of dynamic QoS 127
6.4 Soft-handover 132
6.5 STD performance 139
6.6 Speed-up by event grouping 150
6.7 Conclusions 154
Chapter 7 Conclusions 155
Appendix A Mathematical Derivations 157
Appendix B LRE example behaviour 160
Bibliography 162

Textauszug

Chapter 1 Introduction (S. 1-2)

Communication networks of today must meet high demands regarding the Quality of Service (QoS). Simulative performance evaluation of communication networks is an important means for the design and con.guration of such networks. Other methods of performance evaluation are the measurement of an existing real system and the analytic evaluation of a model describing the target system. Measurement is not possible in the design stage of a system, and analytic methods are usually restricted to very simple models of the target system neglecting some or many possibly important aspects.

In simulation, the complexity of the model and the level of details can be defined flexibly, depending on the aspects the investigation is focused on. Simulations of more complex models, however, are slower than simple models, i. e., they require more run time per simulation time unit. But the question is now, what is meant by slow or fast simulation. It has to be clari.ed what is meant by speed-up, and how it can be de.ned. Assume that results of a reference simulation are available and results from another simulation which has been performed with a certain speed-up technique. The question remains how these techniques can be compared, and some comparison parameter is needed.

This comparison parameter has to be taken from some sorted value space to map the state of the simulation progress to. The progress state the reference simulation has reached when finished, the reference progress state, is mapped to a certain reference value of that value space. The simulation progress state of the other simulation to which the reference simulation is compared also needs to be mapped to that same value space. In fact, for each progress state during the simulation a value is needed. These values are intended to re.ect the statistical accuracy, and on the basis of these values, the simulations can be compared.

If the test simulation reaches the reference progress state in less time than the reference simulation, the test simulation is rated as the faster simulation, or the simulation technique is the faster one. Applying a speed-up technique to a simulation now means, a reference statistical accuracy can be reached in shorter time, or a higher statistical accuracy can be reached within the reference time. The simulation user knows the constraints for conducting simulations. Either the user has a maximum of available time for simulation, or a minimum statistical accuracy is required to manifest a certain statement. In any case, a speed-up technique can either save time or increase statistical accuracy.

The criterion for the statistical accuracy used in this thesis is the relative error for a given range of the value space of the evaluated random variable. The so-called local correlation coef.cient makes a signi.cant contribution to this relative error. Chapter 2 explains the effect of the correlation on the state space coverage and the intrinsic simulation speed-up potential resulting from the systematic reduction of the correlation.

Further, a short introduction on parallelisation is given and the evaluation algorithm Limited Relative Error (LRE) is explained which is of fundamental importance for the investigations of all other chapters. Special speed-up techniques for the simulation of rare events are indispensable. Otherwise, reliable simulation results would not be obtainable within reasonable time. A technique called importance splitting and especially a variant of it called RESTART is introduced in chapter 3. It treats regions of the value space differently in order to reach the relative error limit for each region in a comparable time.

Produkt-Details

• Erscheint lt. Verlag: 17.8.2008
• Reihe/Serie: Advanced Studies Mobile Research Center Bremen
• Zusatzinfo: XXI, 148 p.
• Verlagsort: Wiesbaden
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Wirtschaft
• Schlagworte: Beschleunigung von Simulation • Communication • Information • Kommunikationsnetze • Netzplanung • Simulation • UMTS • Universal Mobile Telecommunications System
• ISBN-10: 3-8348-9513-X / 383489513X
• ISBN-13: 978-3-8348-9513-4 / 9783834895134