# Opportunistic Network Algorithms for Internet Traffic Offloading in Music Festival Scenarios
## 5 Evaluation
### Algorithms and Metrics  
In order to highlight the benefits of our proposed solutions in a festival environment, we compared them with several well-known algorithms previously proposed: Epidemic [11], Spray-and-Wait [4], Spray-and-Focus [25], and Bubble Rap [21].  
The Epidemic protocol operates on a flooding-based scheme. A node exchanges messages with the other nodes in range. The only constraint is that, if a node already has a specific message, it is not duplicated. On the other hand, Spray-and-Wait (SW) bounds the number of message copies allowed to exist at a given time. It has two stages: if the number of copies is greater than 1, a carrier forwards only a part of the message copies to encountered nodes; if there is only one message copy left, the carrier waits to encounter the destination. The first stage can be accomplished in two ways: forward a single copy (the source version of the algorithm) or half of the message copies (binary version) to an encountered node. The binary and source versions of the algorithm will be abbreviated as SWb and SWs, respectively.  
Spray-and-Focus combines the binary version of the spray phase of SW with a utility-based forwarding decision. The utility function replaces the wait phase of SW and uses last-encounter timers in order to decide whether to relay a message or not.  
As was already discussed previously, the Bubble Rap forwarding decision relies on two social metrics: centrality and community structure. Nodes with higher centrality or community members of the message destination will be selected as relays. It is worth mentioning that we have tested Bubble Rap without having nodes store and update a local approximation of each encountered node's familiarity set due to high RAM usage. As a result, community detection is performed based on contact duration and a node's local familiarity set.  
Besides the opportunistic routing protocols proposed and presented in Section 4, we have also tested different combinations of the same ideas, in order to see the differences in performance. There were four criteria which could be applied at different stages of the algorithm (with Table 1, describing the actions performed during each phase of the forwarding decision):  
* Forwarding criterion 1 (FC1)--forward the message if the encountered node is a friend on a social network with the message destination and the carrier node is not;
* Forwarding criterion 2 (FC2)--forward the message if the encountered node has more friends in common with the message destination;
* Forwarding criterion 3 (FC3)--forward the message if the encountered node has a higher centrality;
* Forwarding criterion 4 (FC4)--forward the message if the centrality difference is less than a predefined threshold.  
The performance of the analyzed algorithms is established with the help of the following metrics:  
* Delivery rate--the ratio between the number of delivered messages and the total number of created messages;
* Delivery delay--the time elapsed between the generation of a message and its delivery;
* Overhead--the ratio between the total number of exchanged messages and the total number of created messages;
* Number of hops--the number of nodes through which one message has been relayed until reaching its destination; this metric and the overhead are indicators of the network and node congestion.