# My Smartphone tattles: Considering Popularity of Messages in Opportunistic Data Dissemination
## 7 Performance Evaluation Setup
### Scenario Description  
A social networking app called _Jodel_[7], used by students in a number of German universities, was the basis for our evaluation scenario, simply because of the built in nature of Jodel, where popular jokes among students spread very quickly. We performed an analysis of the collected data using the Jodel app  
Figure 7: The lifetime of good and bad jokes with [PERSON] and Epidemic. (**a**) Initial scenario, with one joke initiator (the happy person in Bremen). (**b**) The behaviour of [PERSON], irrespective of whether the joke was good or bad. Only the people in Bremen received the joke. (**c**) The behaviour of [PERSON], if the joke was bad. Maybe few people around the initiator will get it, but then it will be dropped. (**d**) The behaviour of [PERSON], if the joke was good. Almost everybody will receive it, including far away people in Berlin and Australia. and determined the relevant parameters for this scenario, where we derived our values exemplary from the campus of the University of Bremen. This scenario considers a university campus environment where hundreds of students perform social networking, which is a destination-less OppNets scenario to investigate the spreading of messages in a certain area (refer to Figure 1). The daily life of a student includes visiting a number of locations during an average day at the campus, spread across the campus (lecture halls, labs, cafeterias, library, bus stops, etc.) Each student attends many activities that are spread across the campus. While being involved in these activities, students network with each other in exchanging information related to aspects such as preferences, opinions, new events and helpful information. This information is extremely relevant in the locality and students spread this information based on the relevance or the level of fondness placed on the information. We parameterise our scenario as follows. **Campus Area and Locations**: The campus is a 1.5 km by 1.5 km area, which contains 200 locations consisting of lecture rooms, labs, cafeterias, restaurants, study rooms, bus/tram stops, recreational centres, parks, libraries and administrative offices. **Number of Students**: Although the campus student population is much larger, we opted to use a user group of 500 users considering the users currently using the Jodel app in Bremen. **Message Characteristics and Traffic**: The exchanged messages carry mostly text but may also include an image. New messages are created by users on a regular basis (every 15 min across the network) and are liked or disliked by other users based on their preferences. The size of such messages is 10 KB. **Movement and Characteristics**: When the students are at the university, they walk from one place to another (1.5 m/s) and, once they reach a location, they tend to stay at that location for a time ranging from 20 min to 8 h.  
**Memory Restrictions**: Even if smartphones nowadays have large memory capacities, it is a known problem that users still suffer from problems because of music and pictures stored on their devices. Here, we assume that students are not willing to share much of their storage and limit the cache to 5 MB. Our Jodel-like reference scenario is summarised with all its parameters in Table 2. The parameters we explored in simulation are number of nodes and cache size--two important parameters when it comes to scalability and limited resources.