# Systematic Evaluation of LibreSocial--A Peer-To-Peer Framework for Online Social Networks
## 5 Evaluation of Results
### Effect of the Replication Factor
#### 5.4.1 System Performance  
The analysis of the performance of the system considered the number of nodes in the system throughout the experiment, the hop counts, the number of replicas in the system, the maximum data storage and retrieval times, the message sending and receive rates, the maximum used storage space and the maximum used system memory.  
* Node count: Figure 10a-d portray the behavior nodes in the systems. The figures indicate successful monitoring of the network nodes, and in general the network, which is stable throughout the experimental period. Of note, is the slight reduction by about 100 nodes for both the 1000 and 2000 nodes experiments. A possible reason for this, evident from the logs, is that the nodes experienced insufficient memory errors resulting in overall node failure. However, this did not affect the aggregation of monitored statistics in the network.
* Hop count: The hop count for the experiments are given in Figure 11a-d. In general, the number of hops from sender to receiver is 1 because the number of nodes in the experiments do not exceed the maximum possible limit for the routing table of \(160.20=3200\) entries. Hence the average hop counts tends to be less than one in the network. It is however observed that as the network gets larger, there is less disparity in the network as the graphs show an overlap, as is the case with 1000 and 2000 node graphs.
* Number of replicas: As the number of nodes increases, as can be seen in Figure 12a-d, the number of data replicas data also increases as well. In addition, with increasing replication factor, there is an equivalent increase in the replicas with the same magnitude, which is expected.
* Storage time: From Figure 13a-d, two important observations can be made. First is that increasing the number of nodes results in increased maximum storage time, although the increase is in the order of milliseconds, hence can be ignored. The second more significant deduction is that increasing the replication factor results in increased maximum storage time. In general, the average storage times, as shown in Table 8, are less than one second, but we note the extreme cases of maximum storage time in the order of 10 s of seconds, particularly the 2000 node experiment with replication factor of 4, which recorded a maximum storage time of 91 s. Bearing in mind that storage time includes time to store replicas, it is possible that this discrepancy may be related to storage of data related to distributed data structures such as wall posts and forum threads, which must be distributed and replicated at the same time.
* Retrieval time: This is shown in Figure 14a-d. The same observations as with storage time are also seen here. Again, we make the deduction that large retrieval times are related to distributed data structures. Interestingly, even with more replicas in the network, the maximum retrieval time does not significantly drop. The average system retrieval times are still less than one second. A significant observation is that for the 100 node tests, for replication factor of 16, a higher maximum retrieval time of 15.12 s is seen, in comparison to 0.189 and 0.6 s for replication factors 4 and 32 respectively. It is probable this is the result of a DDS data retrieval and is an outlier.
* Message send/receive rate: From Figure 15a-d, for message sending rates and Figure 16a-d for message receiving rates, it is noted that a higher replication factor there is a drop in the average messaging rates. Also surprising is that when comparing the 100 and 200 node experiments, it seems that a replication factor of 16 seems to generate higher maximum rates than the lower  
Figure 18: Maximum used memory analysis.  
replication factor tests. This result may be an indicator that when considering replication factor, there are values that are accounted as optimum for the network performance. This result may need further investigation. The average rates also dropped as the network became larger, and as the replication factor increased.