# Building Realistic Mobility Models for Mobile Ad Hoc Networks
## 5 Battlefield Simulation Model
### Results and Discussion  
In the previous sections, three different approaches for building simulation models for the evaluation of mobile ad hoc network protocols have been discussed. In order to demonstrate that these models are useful tools in MANET research, the results of running these models using a set of three commonly discussed protocols are presented in this section. In each case, the results from the realistic model are compared with those from using the well-documented random waypoint model under similar circumstances. For each simulation, packet delivery ratio and normalized routing load metrics are used to provide comparisons between the performances of the protocols. The results are also compared across the models to determine whether there are differences in performance that are dependent on the scenario and model being used. The organisation and discussion of the results here follow the common pattern seen in the literature for comparing MANET routing protocols using different movement models, as seen, for example, in [PERSON] and [PERSON], 2012 ([PERSON] and [PERSON], 2012, [PERSON] et al., 2013, ([PERSON] et al., 2013, ([PERSON] et al. be near the rest of his/her fire team, so there will be greater reliance on multi-hop links. The random movements may also result in members of a fire team moving away from each other to different parts of the building rather than moving together. These combined factors will yield more route failures and hence, a lower PDR. When comparing the protocols in greater detail, DSR yields the best performance for both RWP and the realistic model, and the difference between both the models is the smallest. Thus, it has the best packet delivery performance for both movement models. The largest difference between the movement models is when using DSDV. The performance for DSDV is the worst for RWP. However, for the realistic movement model, DSDV outperforms AODV. This shows that the movement model makes a difference when comparing protocols, and it is not possible to merely rely on RWP when selecting an appropriate protocol. The normalized routing load results in Figure 10 show a marked difference in performance among the protocols depending on the model used. The realistic battlefield model outperforms RWP for all the three protocols evaluated (i.e., AODV, DSDV, and DSR). AODV and DSR produce a much larger routing overhead on the RWP model than they do on the realistic model. The comparisons between RWP and the realistic model are as follows: AODV has an NRL approximately five times greater in the RWP model than in the realistic model; DSR produces approximately ten times the routing overhead in RWP than in the battlefield model; and DSDV shows an approximately 30% increase in routing load in RWP than in the battlefield model. Again, the starting point of the nodes is the key issue here. The on-demand protocols (AODV and DSR) have much greater overheads when nodes are spread out from the outset than the proactive protocol (DSDV). Throughout the RWP model, the corporal may be nowhere near the rest of his/her fire team, so more communication will be of the multi-hop type. On the contrary, for the realistic model, the corporal is always near the rest of his/her team, and hence, there is a large amount of single-hop traffic. Obviously, single-hop traffic generates much lower routing overheads, as routing requirements will be resolved within a single hop rather than requiring multiple hops and the propagation of routing requests and replies across the network. Using the random waypoint model, DSR is significantly better than DSDV, but the reverse is true for the realistic model. AODV has the highest routing overhead on both models. Figure 9: Packet Delivery Ratios for our Battlefield Model. RWP: random waypoint method. Battlefield Model Results Summary  
Using RWP to evaluate these protocols using these criteria--node count, space, and simulated time--the following conclusions would be reached.