Impact of Node Mobility in Manet & Analysis of Bonnmotion Mobiliy Models Using Ns3

MANET routing protocol research, greatly depends upon the simulation scenarios based upon node mobility and efficacy of custom protocols developed. Performance of such protocols depends upon how well the real-world mobility models are replicated without degrading the efficacy of the developed protocols. This paper basically explored the impact of node mobility in reinforcement learning based Opportunistic Routing protocols and analysis of mobility models generated using Bonnmotion. The mobility scenario is generated using Bonnmontion 3.0 and simulated using ns3. Analysis of AODV protocols performance is analyzed under various mobility condition and its relation with scenario parameters generated using Bonnmotion. Parameter selection in generating the bonnmotion scenario plays crucial role in mobility model performance and this paper will bring out a wider look upon the importance of parameter selection in Bonnmotion mobility models. Since most of the recent research is based upon Machine Learning concepts, which make use of the dimensions as one criteria for dealing with non-linearity’s. Focus of this analysis is also based upon the importance of 3d mobility models and its importance. Simulation analysis for the Steady state mobility model from ns3 inbuilt model has shown 3.6 Mbps throughput and Inclusion of step time in Probe Random Walk mobility model of Bonnmotion has shown 3.4 Mbps throughput and also with a contrasting result of 100 percentage packet loss when step input is not included. 3kbps increase in throughput is achieved for 3D models when compared to 2D models. This paper will bring out the importance of 3d mobility models and parameter selection impacts from Bonmotion mobility scenario generator.