Network load and traffic pattern on the capacity of wireless ad hoc networks

Abstract

This paper focuses on the capacity of wireless ad hoc networks and analyzes the effect of key factors viz. network size, traffic patterns and detailed local radio interactions on the capacity of such networks. The capacity is evaluated with several different network layouts and traffic patterns through simulations. To demonstrate the impact of these factors, the capacity evaluation starts with a simple case of a chain of evenly spaced nodes in a network environment and progresses to a network with random traffic and randomly spaced nodes. Initially, capacity of static nodes is evaluated for various network layouts and traffic patterns. Since, in most scenarios, nodes do not travel significant distances during packet transmissions. As an enhancement, mobility of nodes is introduced into the network scenario and the performance is again evaluated. The simulations are carried out using OPNET modeler and the results obtained are presented in this report. The results are analyzed to understand the impact of these factors on the capacity and consequently suggest measures to increase the same. This work shows that the achievable capacity of ad hoc network depends on network size, traffic pattern and mobility. In a single cell topology, it is found that there is a 50% reduction in network throughput, if the node size increases from 2 to 10 nodes, whereas there is a 74% reduction in the throughput for chain topology for the same increase in node size. In a lattice topology with horizontal traffic, there is a 46 % reduction in network throughput when the lattice size increases from 4X4 to 5x5.The same percentage of reduction is observed when both horizontal and network traffic is introduced. In a random network topology with random traffic, there is an 80 % reduction in network throughput when the node size increases from 150 to 750 nodes. However, for the same scenario with the introduction of mobility to the nodes, a slight improvement is achieved with an overall 75% reduction in network throughput.