## 5 Results from Experiments Using the Platform
### Further Discussion and Real-World Effects  
Of course, the main reason for employing an experimentation platform is not to replicate results from simulations but rather to study the impact of real-world effects and imperfections, something not possible with simulations. Here, this aspect is demonstrated by exploring the impact of localization accuracy through a comparison of the performance results across the three configurations. Indeed, the simulated mobility in the first configuration sets a benchmark for perfect localization, while the second and third configurations capture settings of increasingly coarser localization accuracy due to the characteristics of the GPS devices employed in each case. The results indicate clearly that, while all three configurations exhibit the same trends, the performance of all protocols degrades as the localization accuracy becomes coarser. This occurs because message-carrying nodes select next hops on the basis of partially incorrect position information, and this leads to sub-optimalor even inappropriate message forwarding decisions. It is interesting that, in some respects, the reduced performance due to imprecise localization manifests itself as a smaller network density. Indeed, as remarked earlier, lower network densities are also associated with a degraded performance of all routing protocols because of the reduced number of potential message-forwarding opportunities. However, the connection is stronger, as now explained: By considering the delay-related performance results for each configuration alone, one may determine the value of the density for which the delay curves of MFR and MoVe intersect. Since the carry-based MoVe performs better in sparse topologies and the forward-based MFR in dense ones, the value of the density at the intersection characterizes the transition from sparse to dense topologies, i.e., intermediate regimes for which both the forward and carry actions have a significant impact. In light of this, the results demonstrate that the value of the \"transitional\" density becomes greater for configurations with more inaccurate localization. In other words, a given network topology will appear to be sparser when the localization becomes less precise. We point out that the performance impact of the localization inaccuracy has been represented somewhat emphatically in the results just discussed due to particular characteristics of the relevant experiments. Specifically, although the GPS units employed in the second and third configurations are typical devices featuring a modest degree of imprecision (2.5 m for NEO-M8N and 3 m for VK-162, see Section 3.2.3), the effect of this imprecision becomes pronounced in the context of the experiments, due to the comparably small size of the mobility terrain (14 \(\times\) 14 m, also restricting the magnitude of the distances between nodes) and of the communication ranges employed (3-7 m, also restricting the extent of a node's neighborhood). If the same GPS devices had been used in setups involving larger terrains and longer communication ranges, the impact of localization inaccuracy would have been milder; the same performance trends would still have been present but to a lesser extent. In the same spirit, it is seen that the small-size experiments discussed here, besides their capability for emphasizing the effect of location inaccuracies, are also useful in demonstrating that the performance of all considered routing protocols degrades gracefully, even when the information on the positions of candidate next-hop nodes becomes highly inaccurate (in relative terms). We close by presenting results from one more experiment, again representative of real-world aspects that can be studied with the help of the platform. For this experiment, the central part of the mobility terrain was blocked by means of a square obstacle of size 6 \(\times\) 6 m placed therein (see Figure 15).