Fundamental features of ad hoc networks' simulations

• Authors: Tapio Frantti;Mirjami Taramaa
• Venue: DNCOCO'06 Proceedings of the 5th WSEAS international conference on Data networks, communications and computers
• Year: 2006

ods in description of complicated real-world phenomenons. There are multiple reasons for that such as dramatic increase in processing power and significant decrease of price of the computing systems and the fact that the probability theory is a well-known tool for presentation and processing of stochastic information. As a primary aim, in this article is described fundamental stochastic features of the ad hoc network simulations. Especially, a concept of convergence time of simulation models is considered. It refers to the minimum simulation time required for the reliable results. Its practical numerical model-based evaluation is defined by example simulations. Ad hoc network models considered here are event based discrete time models, which utilize Markov chain theory for the definition of state transitions and Monte Carlo random sampling method for the definition of events probabilities and duration times of them. Numerous reported case studies of the network simulations do not contain any information about the convergence time of the model. In some publications results are achieved by very short simulation times spanning from a few seconds only to tens of seconds. Moreover, the same simulation times are used for different sizes of networks. However, the convergence time even for a moderate size of ad hoc networks, such as 10 nodes, may be thousands of seconds and it increases as a function of nodes as will be shown in this paper. The secondary aim of the paper is to optimize IEEE 802.11b AODV (Ad hoc On demand Distance Vector) based network throughput by parameters optimization. In simulations, it was noticed that RTS/CTS (Ready to Send/Clear to Send) threshold initiation and active route timeout parameters had significant influence to the overall throughput in small networks.