## 4 Simulation And Analysis
### Analysis of Experimental Results
From Figure 8c, the gap of average end-to-end delay between FPRDM and FCNS reaches the maximum of 60 s when \(N=300\), which indicates that the fuzzy control strategy of the FPRDM scheme is superior to that of the FCNS algorithm. To be specific, the FCNS algorithm focuses on node similarity, which is a flexible metric due to the changes in nodes attributes; while the FPRDM scheme considers the fuzzy data transmission relationship between nodes through their social online features, which can be converted into a digitized index and utilized to make a more reasonable data transmission decisions in OSNs. Besides, with the application of the mechanisms of node cooperation and cache management, the ICMT algorithm is able to maximally and rationally utilize the buffer memory space of each  
Figure 8: Performance Please comparison of average end-to-end delay with various cache spaces and various number of nodes. B: Spray and wait; C: Epidemic; D: ICMT; E: FCNS; F: FPRDM **(a)**\(N=100\). **(b)**\(N=200\). **(c)**\(N=400\). **(d)**\(N=600\). node, and more importantly, tremendously improving the efficiency of the data dissemination and simultaneously decreasing the average end-to-end delay. Finally, we explore the performance comparison of the network overhead from the five routing schemes with various cache spaces and various number of nodes. As demonstrated in Figure 9, when the buff memory space of nodes constantly increases from 10 to 40 Mb, the network overhead from each algorithm declines dramatically. On the contrary, when the number of nodes in the communication area continually increases, the network overhead of each algorithm slowly goes down. As exhibited in Figure 9, the network overhead of these algorithms could be ranked from high to low as: Spray and Wait, Epidemic, ICMT, FCNS, and FPRDM. Specially, the network overhead of the FPRDM algorithm is always the lowest among these methods, presenting an average network overhead of 150. From Figure 9a, when \(N=100\) and \(C=40\) Mb, the network overhead of the FPRDM scheme reaches the minimum value of 50, which means that this strategy adopts fuzzy inference theory to effectively control the number of message replications and simultaneously reduce the number of relay nodes. From Figure 9d, when \(N=600\) and \(C=10\) Mb, the network overhead from the Spray and Wait approach reaches the maximum approximately 660. When selecting a suitable relay node, the Epidemic routing algorithm adopts the flooding model to widely spread data packages in the network. ICMT, Spray and Wait, and FCNS employ data management, encountering history, and fuzzy control to make a more accurate decision on message routing and forwarding, respectively. This is because message replications are widely propagated in the Spray phase, while in the next phase the number of messages is tightly controlled, thereby resulting in an increase in the number of hops. Besides, the network overhead from ICMT and FCNS routing algorithms is in the middle level all the  
Figure 9: Performance comparison of network overhead with various cache spaces and various number of nodes. B: Spray and wait; C: Epidemic; D: ICMT; E: FCNS; F: FPRDM. (**a**) \(N=100\). (**b**) \(N=200\). (**c**) \(N=400\). (**d**) \(N=600\). time, because some effective message controlling strategies such as information management, fuzzy routing selection have been adopted. To sum up, the experimental results demonstrate the proposed scheme reduces the network delay and the overhead ratio, and increases the delivery ratio as compared with several typical and latest routing protocols. Especially, in the best case, the proposed scheme presents an average delivery ratio of 0.8, reduces the average end-to-end delay by nearly 45% as compared with the Epidemic routing protocol, and lowers the network overhead by about 75% as compared to the Spray and Wait routing algorithm.