## 4 Evaluation
### Replication Techniques and Average Delivery Delay  
It is also important to note that average delivery delay increases with more message copies (cf. Figure 18) and may be controversial to expected results. The computation of average delivery delay is unaware of message copies and treats multiple deliveries of the same message as deliveries of different messages. As a result, the average delivery delay increases when a destination node receives additional copies of a message that has already been delivered, which becomes more frequent with higher delivery guarantees. Hence, delay is incurred from retaining messages until more suitable relay nodes are encountered.  
Take Figure 20 for example, which illustrates two scenarios that involve sending a message from source to destination. A maximum of 2 copies are generated in the first scenario, while the second scenario generates up to 4 copies. Also assume that 1 copy of the message is lost in each scenario. For the first scenario, the average delivery delay is only determined by the time taken to deliver the remaining copy. On the other hand, the average delivery delay in the second scenario is determined by the time taken to deliver each of the remaining 3 copies. Consequently, the average delivery delay is higher in the second scenario, even when the first copy of the message was delivered in less time. While this method of computing average delivery delay is reasonable for OppNet applications like interest-based or location-based data dissemination (i.e., it shows how long it takes for copies the message to reach interested or intended users), it may not be suitable for applications such as sensed data collection where a successful delivery is determined by receiving only one copy of the message. In order to prevent misleading results, whether or not the computation of average delivery delay considers multiple deliveries as unique deliveries needs to be based on the OppNet application at hand.  
As shown in Figure 18, PRoPHET without a replication technique records the lowest average delivery delay. Without a replication technique, message loss due to buffer overflow is more frequent (especially when they are dropped according to the FIFO policy), thereby curbing most of the delay that results from retaining messages until better relay nodes are encountered. Fixed-quota replication reduces message loss due to buffer overflows by transferring custody of a message to a relay node in the focus phase (i.e., after the quota is exhausted). Hence, even when there are 8 copies of each message in the network, buffer overflow is still limited. In terms of delay however, more quota retains messages in node buffers for longer periods. While this utilizes more encounter opportunities to increase throughput, more average delivery delay is incurred each time the replication quota is increased. However, transferring custody of a message to a relay node in the focus phase also limits the throughput of fixed-quota replication (as compared with LARep) since better encounter opportunities that may arise afterwards are missed. On the other hand, retaining some messages for longer periods causes LAMeD to incur a higher average delivery delay, and the replication mechanisms in LARep introduces more delay by generating more copies of certain messages.  
Figure 19: Number of failed transmissions (aka. aborted messages in ONE simulator) in the Skudai scenario.