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Lecture Wireless and mobile computing – Chapter 27: Wireless and mobile computing simulations

Chapter 27 - Wireless and mobile computing simulations. The following will be discussed in this chapter: What is ns-2? Getting ns? How to use ns-2? Adding your own stuff? Documentation, bug-fixing, fundamentals of discrete event simulation, ns-2 simulation. | Wireless and Mobile Computing Simulations Lecture 27 Overview 2 Motivation: Learn fundamentals of evaluating network performance via simulation fundamentals of discrete event simulation ns-2 simulation Overview: What is ns-2? Getting ns? How to use ns-2? Adding your own stuff? Documentation Bug-Fixing 3 4 Network Simulation Motivation: Learn fundamentals of evaluating network performance via simulation Overview: Fundamentals of discrete event simulation ns-2 simulation 4 5 What is simulation? 6 Why Simulation? Real-system not available, is complex/costly or dangerous (e.g: space simulations, flight simulations) Quickly evaluate design alternatives (eg: different system configurations) Evaluate complex functions for which closed form formulas or numerical techniques not available Simulation is a flexible methodology we can use to analyze the behavior of a present system or proposed business activity, new product, manufacturing line or plant expansion, and so on (analysts call this the system under study). By performing simulations and analyzing the results, we can gain an understanding of how a present system operates, and what would happen if we changed it -- or we can estimate how a proposed new system would behave. Often -- but not always -- a simulation deals with uncertainty, in the system itself, or in the world around it. 6 Simulations Types Discrete Simulations Monte Carlo Simulation Discrete Event Simulation, In the field of simulation, a discrete-event simulation (DES), models the operation of a system as a discrete sequence of events in time. Each event occurs at a particular instant in time and marks a change of state in the system. Between consecutive events, no change in the system is assumed to occur; thus the simulation can directly jump in time from one event to the next. Monte Carlo methods rely on random sampling of values for uncertain variables, that are "plugged into" the simulation model and used to calculate outcomes of interest. 7 8 . | Wireless and Mobile Computing Simulations Lecture 27 Overview 2 Motivation: Learn fundamentals of evaluating network performance via simulation fundamentals of discrete event simulation ns-2 simulation Overview: What is ns-2? Getting ns? How to use ns-2? Adding your own stuff? Documentation Bug-Fixing 3 4 Network Simulation Motivation: Learn fundamentals of evaluating network performance via simulation Overview: Fundamentals of discrete event simulation ns-2 simulation 4 5 What is simulation? 6 Why Simulation? Real-system not available, is complex/costly or dangerous (e.g: space simulations, flight simulations) Quickly evaluate design alternatives (eg: different system configurations) Evaluate complex functions for which closed form formulas or numerical techniques not available Simulation is a flexible methodology we can use to analyze the behavior of a present system or proposed business activity, new product, manufacturing line or plant expansion, and so on (analysts call this the