Temporal Modeling of Node Mobility in Mobile Ad hoc Network

Abstract

Ad-hoc network consists of a set of identical nodes that move freely and independently and communicate via wireless links. The most interesting feature of this network is that it does not require any predefined infrastructure or central administration and hence it is very suitable for establishing temporary communication links in emergency situations. This flexibility however is achieved at the price of communication link uncertainties due to frequent topology changes. In this article we describe the system dynamics using the proven concept of time series modeling. Specifically, we analyze variations of the number of neighbor nodes of a particular node over a geographical area and for given total number of nodes assuming different values of (i) the speeds of nodes, (ii) the transmission powers, (iii) sampling periods and (iv) different mobility patterns. We consider three different mobility models: (i) Gaussian mobility model, (ii) random walk mobility model and (iii) random way point mobility model. The number of neighbor nodes of a particular node behaves as a random variable for any mobility pattern. Through our analysis we find that the variation of the number of neibhbor nodes can be well modeled by an autoregressive AR$(p)$ model. The values of $p$ evaluated for different scenarios are found to be in the range between $1$ and $5$. Moreover, we also investigate the relationship between the speed and the time of measurements, and the transmission range of a specific node under various mobility patterns.