## 4 Experimental Design
### Experiment Implementation
#### 4.2.3 Communication Behavior
The red line shows the beacon threshold, or the maximum number of non-beacons (_i.e._, 75). The blue line shows the number of non-beacons with an average fitness over 60; these nodes represent how many nodes know their position with a degree of confidence acceptable for our model. The green line, on the other hand, shows the number of non-beacons with fitness over 20, representing all the nodes that know their position even if it is not dependable, _i.e._, the accumulated positioning error over time is too great for their position to be accurate. Results show that, on average, around 50% of the nodes present in the scenario shown on Figure 7a (25 beacons and approximately 25 non-beacons) are able to estimate their position with acceptable confidence, _i.e._, with decay over 60. In addition, about 35% of non-beacons know their position with decay between 20 and 60, although their positioning information would be of no use for collaboration under our model. The energy consumption of each device has been represented using an arbitrary unit count. Each of these arbitrary units is associated to an energy cost of around \(166\pm 0.04\%\)\(mW\)[40] (depending on the type of antenna used), and thus, each time an arbitrary unit is added, it is in fact representing expended energy. This is done to avoid setting a fixed energy value for all nodes, given that not all devices use the same type of peripherals in real-world scenarios. The energy unit count is initialized at 0 at the beginning of the simulations, and increases as time passes, and also each time a peripheral is used either to sense or to communicate. Figure 7b shows the accumulated energy consumption values (in arbitrary units) in a scenario with 25% beacons and a communication range of 50%. The GPS (Real) curve represents the energy utilization of the GPS in a real-world scenario, while the GPS (Model) curve is the approximation that has been achieved on the simulation. Results from GPS (Real) and GPS (Model) should be identical or at least

Figure 7: **(a)** Average node count and **(b)** average energy consumption for the scenario. similar, given that both represent the same variable (the first obtained from literature, the other from the simulation). However, there is a difference of 111 arbitrary units (18,547.54 mW) between these curves, which means the approximation from the simulation is off and must be corrected to provide more accurate values for energy consumption. It is important to note that the Collaboration curve, which represents the energy consumption of a non-beacon node, is unexpectedly 69 arbitrary units (11,571.86 \(mW\)) below the goal energy consumption, represented by the GPS (Model) curve. ## 6 Limitations of the Model

This section details the limitations of the proposed model; for each of them we discuss its impact on our research, and possible ways to overcome them in future work. (1) All of the research has been performed through simulations of outdoor environments, which could be different from a real disaster relief scenario. However, the models used in the simulations are well accepted by the research community; in particular, the mobility model used for the nodes was the most accepted one for disaster scenarios. (2) The model is focused on outdoor scenarios and positioning strategies, and does not address aspects involved in indoor positioning. Since most indoor positioning systems rely on electricity and infrastructure-based communication networks, which could be damaged or collapsed and thus unavailable, they have not been taken into account. However, given that the model is detached from the actual positioning, indoor strategies could be considered in further iterations of the model if required. (3) The current version of the positioning model does not address the security and privacy concerns related to the shared information; therefore, it could be used to track users, or even to deceive users with false information.