Temporal Modeling of Link Characteristic in Mobile Ad hoc Network

Abstract

Ad hoc network consists of a set of identical nodes that move freely and independently and communicate among themselves via wireless links. The most interesting feature of this network is that they do not require any existing infrastructure of central administration and hence is very suitable for temporary communication links in an emergency situation. This flexibility, however, is achieved at a price of communication uncertainty induced due to frequent topology changes. In this article, we have tried to identify the system dynamics using the proven concepts of time series modeling. Here, we have analyzed variation of link utilization between any two particular nodes over a fixed area for different mobility patterns under different routing algorithm. We have considered four different mobility models -(i) Gauss-Markov mobility model, (ii) Manhattan Grid Mobility model and (iii) Random Way Point mobility model and (iv) Reference Point Group mobility model. The routing protocols under which, we carried out our experiments are (i) Ad hoc On demand Distance Vector routing (AODV), (ii) Destination Sequenced Distance Vector routing (DSDV) and (iii) Dynamic Source Routing (DSR). The value of link load between two particular nodes behaves as a random variable for any mobility pattern under a routing algorithm. The pattern of link load for every combination of mobility model and for every routing protocol can be well modeled as an autoregressive model of order p i.e. AR(p). The order of p is estimated and it is found that most of them are of order 1 only.

The Effect of Mobility Models and Traffic Patterns on the Performance of Routing Protocols in MANETs

“…The movement of mobile nodes may lead to breakup of communication links between source and destination [2]. The statistical behavior of physical movement of mobile nodes are described by diff erent mobility models like Random Way Point (RWP) [3,4], Reference Point Group Mobility (RPGM) [6], Manhattan Grid (MG) [5] and Gauss-Markov (GM) [7]. A survey of diverse array of mobility models is introduced in [8].…”