From: Richard Whitehouse Date: Fri, 13 May 2011 10:06:15 +0000 (+0100) Subject: Improved network simulation section. Will move large part of content to prep chapter X-Git-Url: https://git.richardwhiuk.com/?a=commitdiff_plain;h=6e0b6ac6784280cf9f8254fce67bb39e1a7afdc6;p=ii-diss.git Improved network simulation section. Will move large part of content to prep chapter --- diff --git a/introduction.tex b/introduction.tex index 5e434c9..e09840b 100644 --- a/introduction.tex +++ b/introduction.tex @@ -88,18 +88,9 @@ Network simulation is a evolving area of research, with many different simulator There are a number of different approaches to simulating a computer network architecture. The first is discrete event simulation. Here a simulator is primed with a topology and a number of event sources. These event sources fire events, which are executed in turn, which may then fire other events. The events are stored in a priority queue. Each event is executed according to it's time, with a global variable containing the current time of the simulation being advanced upon the executing of each event. This is continued until either there are no more events left in the queue, or some predefined time has passed. This simulation technique has the advantage that areas in which nothing of interest are passed over quickly, while events which are notable are where the majority of the computation is spent. -Other types of network simulation include markov chain simulations which are useful for modelling queueing +Other types of network simulation include markov chain simulations which are useful for modelling queueing systems. These depend on systems with little state that can be modelled by a stochastic process. This isn't the case for packet simulation, where there is a large amount of state and no overall defined equation across the entire simulation. - -Network simulation is a hot area of research activity with many different simulation techniques identified. I have chosen to use network simulation instead of using a different evaluation technique like building a real life model of the networks under simulation due to the large number of hosts required which would be impractical in terms of cost. Network simulation poses a viable alternative, especially if a well known and tested network simulator is used. - -The two main types of network simulators are discrete event simulators and - -Since no implementation of MOOSE exists for a current network simulator, I will need to program this module and make checks to ensure it produces valid data. - -In terms of simulation, I shall be using a discrete event simulator, in which events are added to a priority queue, with the lowest item being taken off the queue and processed. Each event may generate future events which will be processed until a finish condition is reached at which point the simulation will terminate. - -Simulation has a number of drawbacks. Primarily it is not a perfectly accurate representation of the underlying system and so I will need to make sure that my simulation is valid for the measurements I take. +A further type of simulation is continuous simulation where the timestep is incremented, and events ocurring between the two states are modelled. This works well for physical phonomena, such as radio waves or propogation of signals in wires where the situation is continually evolving. However, they spend the same processing power on all periods of time during the simulation, whether the period is one of high activity or low activity. Also, in order to get a good representation of the underlying phonemena, you have to use very small time increments which gives a high simulation cost. \section{Context}