tailieunhanh - Hiệu suất của hệ thống thông tin máy tính P18

In the previous chapters we have addressed models that can be solved by analytical or numerical means. Although the class of addressed models has been very wide, there are still models that cannot be solved adequately with the presented techniques. These models, however, can still be analysed using simulation. With simulation there are no fundamental restrictions towards what models can be solved. Practical restrictions do exist since the amount of computer time or memory required for running a simulation can be prohibitively large | Performance of Computer Communication Systems A Model-Based Approach. Boudewijn R. Haverkort Copyright 1998 John Wiley Sons Ltd ISBNs 0-471-97228-2 Hardback 0-470-84192-3 Electronic Part V Simulation Performance of Computer Communication Systems A Model-Based Approach. Boudewijn R. Haverkort Copyright 1998 John Wiley Sons Ltd ISBNs 0-471-97228-2 Hardback 0-470-84192-3 Electronic Chapter 18 Simulation methodology and statistics In the previous chapters we have addressed models that can be solved by analytical or numerical means. Although the class of addressed models has been very wide there are still models that cannot be solved adequately with the presented techniques. These models however can still be analysed using simulation. With simulation there are no fundamental restrictions towards what models can be solved. Practical restrictions do exist since the amount of computer time or memory required for running a simulation can be prohibitively large. In this chapter we concentrate on the general set-up of simulations as well as on the statistical aspects of simulation studies. To compare the concept of simulation with analytical and numerical techniques we discuss the application of simulation for the computation of an integral in Section . Various forms of simulation are then classified in Section . Implementation aspects for so-called discrete event simulations are discussed in Section . In order to execute simulation programs realisations of random variables have to be generated. This is an important task that deserves special attention since a wrong or biased number generation scheme can severely corrupt the outcome of a simulation. Random number generation is therefore considered in section . The gathering of measurements from the simulation and their processing is finally discussed in Section . The idea of simulation Consider the following mathematical problem. One has to obtain the unknown area a under the curve y f x x2. from x 0