# Opportunistic Network Algorithms for Internet Traffic Offloading in Music Festival Scenarios
## 3 A Festival Mobility Model
### A Proposed Festival Mobility Model (FMM)  
The model that we propose here borrows the concept of an interaction matrix from CMM. The matrix can also be derived from social investigation, besides generating it with social network models. In our case, this social information, which shows how many of a person's Facebook friends have attended a festival, was gathered using a form with 67 valid answers. The survey asked participants what festivals they attended in the last year and, through Facebook check-ins, which of their social network friends also participated. The results of the survey show that the majority of people participating in this study have between 3 and around 50 Facebook friends that attended the same festival as them, as can be observed in Figure 3.  
The information provided by this form has been used as a pool of values when assigning the number of friends to a node. The weights of the interaction matrix have been generated randomly, but making sure a node is part of a custom-sized community. The second step of CMM has been skipped and the communities have been established along with the number of friends per node. It was assumed that a person attending a festival has around five close friends who form its community. The reason behind choosing 5 as the average community size is the result of a study on human social behavior at large-scale events [19]. The event where the experiment took place was an 8-day 6-stage music festival with 130,000 attendees. A part of this research was to model the crowd's internal structure with the help of a community discovery algorithm. The groups are defined as sets of people that are frequently located in the same spatio-temporal bins. The model consists of directed graphs, with the weight of an edge being defined as \"the number of co-occurrences of participant \(A\) with participant \(B\) divided by total number of occurrences of participant \(A\)\" [19]. For an edge to be accepted as valid, a constraint was imposed, which specifies that the only links chosen were the ones that occurred in more than two different locations, with a weight of at least 0.5 [19]. After employing a rewiring algorithm [20] and performing 35 tests, the conclusions were that the average group size was 5 (with a standard deviation of 4.32) and the average number of links for a node was 3 (with a standard deviation of 2.60). A rewiring algorithm is  
Figure 3: Number of Facebook friends attending a festival. the process of creating a randomly generated network from an existing network while preserving some of its topological properties, such as the degree of nodes, so one can focus only on certain aspects of the network design instead of dealing with the whole complexity of the system. The groups are assigned randomly to a cell in the grid, but not without taking into account the density of the crowd. A crowd safety and risk analysis study [15] conducted in 2019 shows that the upper limit for standing/viewing spaces is 5 people per square meter. The study also maps different densities of people per square meter. For this model, 4 ppsm (people per square meter) has been chosen as the upper limit for the most crowded areas at a festival, usually registered near the stage. 3 ppsm has been chosen as an intermediary density, as the distance to the stage increases. 2 ppsm will be the minimum density, used for the back rows of a crowd. Another shortcoming of the implementation of HCMM, which emerges from the fact that a cell can host only one community, is that the members of that community are randomly placed in that cell, sometimes at distances that would not comply with a festival crowd distribution. One important aspect of our proposed festival mobility model is the way it handles crowd distribution. First of all, depending on the position of the stage (assumed to be in the north of the grid), the model computes a maximum number of hosts per cell based on the three values for crowd density mentioned earlier.