## 5 Simulation Scenarios  
The ns-2 [46] simulator was used during this validation process because it allows us to model several network scenarios and collect statistics through trace files. The OLSR model and also the model used by the ns-2 simulator to evaluate the network performance are described in [47]. Using this simulation tool we defined several network topologies, configure wireless network interfaces and set the node mobility patterns. The node mobility was modeled using the BonnMotion simulator [48], due this tool includes well-known models that represent people mobility in the studied scenarios. The mobility models considered in this work have a widely analyzed and validated mathematical basis [49; 50; 51]. For the simulations, we have considered two physical areas that represent regular interaction spaces in our everyday life. The first one is a square open area of 300 \(\times\)300 m that represents a beach area or a park (Figure 2), where people are free to move throughout the whole space, and eventually interact with other people (e.g., friends or relatives) in that area. In this scenario the people (_i.e._, the nodes of a HWSN) can remain stationary during a picnic, or walking with or without a clear direction. Figure 2 shows some matches between people that know each other (_i.e._, human-based sensors). A mobile collaborative application that detects the presence of these people can eventually trigger impromptu interactions among them. The second scenario is also an open area, similar to a pedestrian promenade, but represented by a rectangle of 30 \(\times\)3,000 m. In such a scenario the people can stay for a while (e.g., sharing a drink) or walking through the area (Figure 3). In this place, most pedestrian movements follow a pathway, and people can move in both directions. Both interaction scenarios have the same size (90,000 square meters), which allows us study the influence of the area shape on energy consumption, by keeping the same node density in the interaction space. The simulations in those scenarios considered a HWSN composed of 10, 20, 30 and 40 nodes respectively, which form various islands according to the people movements. The behavior of these nodes alternate between some periods where they are stationary and others in which they move up to 1, 2, 4 or 6 m per second (mps). The nodes movement can follow one of the following mobility models: _Random Walk_, _Self-similar Least Action Walk_ (SLAW), _Nomadic_ or _Referen  
Figure 2: Potential interactions scenario in a park. (RPGM) [48]. These mobility models are quite representative of the movements that we can expect of a person or those of a group in the studied scenarios. The Random Walk model considers people moving randomly in terms of direction and speed, within a certain area [49]. This model illustrates the movements of people in a park, where each person can move via walking, running or riding a bicycle without using formal paths. In the SLAW model the people move quite randomly, but they are aware of the speed and direction of their movements. This is similar to the movements of people that use the walking paths of a park. This model is also effective in representing casual encounters among community members; e.g., students at the university campus or friends in a theme park [50]. The Nomadic model considers people moving in groups from one location to another. This is representative of guided tours at a city downtown or a museum, where the tourists move together visiting several interest points [49]. This model considers a particular node per group (_i.e._, a reference node) that determines the next target point, and also a reference path and speed to reach such a place. Such a role can be played by the tour guide. The RPGM model is similar to the Nomadic, however in this model there is no reference node; therefore the entire group determines its motion behavior (including location, speed, direction, acceleration, _etc._) according to its goals [51].