The Performance of MANET Routing Protocols with Different Mobility and Propagation Models

Simulation tools are primary means for evaluating and analysing performance of Mobile Adhoc NETworks (MANETS). Different mobility and propagation models have been used in this context. However, simple propagation models have been used heavily in simulation based MANETS routing performance analysis. A range of propagation models (such as ITU-R P.1411-5, ITU-R P1238-6, GOA-LoS, modified TRG, C-Shadowing and WINNER) for various indoor/outdoor and LoS/NLoS scenarios have been added into ns-2 based simulation and results have been analysed with those readily available in the simulator for AODV, DSR and OLSR routing protocols. A variety of synthetic mobility models have been implemented under those pathloss conditions and their impact on routing performance has been observed. Heterogeneous mobility conditions have been introduced for performance analysis of AODV and DSR routing protocols under, TRG, ITU and GOA pathloss conditions. It has been found that the DSR protocol fails to perform where AODV prevails in specific mobility environment. RPGM model have been analysed with variations of mobility model adopted by group-heads and its impact on MANETS have been investigated. A very large adhoc network has been tested through ns-2 simulator with comparison of ITU and TRG channel loss conditions and its results have been compared with other scalable routing performance analysis studies. Impact of corner-loss effects due to typical street movement scenario such as under MG mobility have been experimented through ITU-R based recommendations in ns-2 simulation environment. A small testbed based AODV performance analysis has been compared with ns-2 based simulation results under ITU and Shadowing propagation models and significant difference have been recorded in real vs simulation based results for NRL and Mean. Delay analysis. In summary, MANET performance have been analysed under a range of operational conditions and applications and it has been demonstrated that various factors such as mobility and propagation environment could significantly challenge the deployment of such networks