# An Adaptive Delay-Tolerant Routing Algorithm for Data Transmission in Opportunistic Social Networks
## 4 Simulation
### Analysis of Experimental Results
#### 4.2.2 Performance Comparison between the Five Algorithms  
In this section, we provide a fair comparison on the performance of the five algorithms based on the same simulation environment, and analyze the distribution of error, standard deviation, etc. To this end, the accuracy of experimental results can be guaranteed. As shown in Figure 6, the delivery ratio from the Epidemic algorithm is lower than that from the other algorithms all the time. The reason for that is Epidemic is based on the flooding model, under which massive data groups lead to network congestion and performance degradation. The delivery ratios from P&F and Spray and Wait are at the medium horizon all the time. This is because they utilize a two-phase mechanism to control the number of message duplicates and then to avoid data congestion. Figure 5: The remaining cache comparison between five algorithms with various number of nodes. Figure 6: Delivery ratio comparison from five algorithms with various cache spaces. As we seen in Figure 6, THE delivery ratio from DTCM is approximately 0.75 as the cache increases from 10 to 35 Mb. DTCM evaluates the ability of each node to process messages through cache and energy and adopts a comprehensive fuzzy evaluation method to determine the special relationship between the two-factor and data transmission. More reliable relay nodes participate in the data transmission process, so the total number of hops from source to destination decreases and the delivery ratio is improved. When the cache space is 15 Mb, the delivery ratio from FCNS is higher than that from DTCM, because FCNS improves the selection of relay nodes through their similarity. However, FCNS cannot handle the data congestion when the size of cache space increases from 15 to 30 due to its simple structure. Figure 7 plots distribution of errors from experiments on delivery ratio comparison. From Figure 7, it is shown that those errors obey an approximate normal distribution and converge to 0.078 with the increases of the duration of the experiment. This is an acceptable fault tolerance interval of 0.05-0.1. Then, the performance evaluation comparison between the five algorithms in terms of average end-to-end delay is exhibited in Figure 8. As the cache space increases from 10 to 35 Mb, average end-to-end delay from Epidemic, FCNS, and P&F algorithms is higher than that from DTCM and Spray and Wait. Due to the small amount of data transmission, the delay from Spray and Wait is closest to the optimal. As a type of two-phase scheme, P&F involve a special period that is known as \"wait stage\", in which a long waiting for destination will increase the end-to-end delay. Epidemic demonstrates an average end-to-end delay of about 140 min because of a large of message duplic  
Figure 8: Average end-to-end delay comparison from five algorithms with various cache spaces. Figure 7: Distribution of error from the experiments on delivery ratio comparison. As shown in Figure 8, the fuzzy inference system in DTCM is helpful in reducing the influence of independent variable change on decision uncertainty. To this end, the average end-to-end delay from DTCM remains a relatively low level all the time. FCNS is significantly inferior to FCNS in term of average end-to-end delay. On the one hand, energy and cache space are two of the most significant metrics to be considered in the data transmission process. On the other hand, the structure of curve-trapezoidal distribution adopted by CMFI is simpler than that of the normal distribution used in FCNS, which meets the requirements of low computing and low energy consumption in most mobile devices. Overall, average end-to-end delay from DTCM decreases nearly 25% than that from FCNS. In Figure 9, the dots represent the distribution of standard deviations from multiple experiments, and the horizontal line represents the mean of these standard deviations. The mean of standard deviation from DTCM and Spray and Wait are about 0.8 and 0.9, respectively.