## 5 Performance Analysis
### Performance Analysis of Caching Mechanisms  
The state-of-the-art mechanisms cache the content in several inefficient ways (e.g., LCE caches the content to all the traversed network devices or LCD caches the content only in the traversed neighbor node). Therefore, the duplicate content increases the memory consumption, but it also increases the content hit ratio in case of LCE. There are several inefficient cache replacement algorithms (e.g., least recently used (LRU), first in first out (FIFO), and last in first out (LIFO)). As a result, the probability of content replacement from the cache memory is very high in the dense network area. These cache replacement algorithms are directly related to the content hit ratio that was used in several state-of-the-art mechanisms. Therefore, the probability of replacement of the most popular content was increased. However, our proposed mechanism provides better caching efficiencies in terms of caching popular content. The detailed description of the proposed solutions based on the cluster-based mechanism was already shown in Figures 6 and 8. In Figure 9, we also showed the performances of our proposed, on-path and the state-of-the-art caching mechanisms in terms of content transfer time. A small video file was used as video traffic to evaluate the content delivery time for all mechanisms. It is clear from Figure 9 that our cluster-based approach required less content transfer time than state-of-the-art mechanism if the content is not available in the cache memory in case of the basic LCE. The content transfer time in the LCE mechanism is equal to our cluster-based CCN but the memory consumption, bandwidth consumption, network congestion, and flooding the network reduces the overall network efficiencies. Therefore, the cluster-based CCN provides a better solution than the existing simulated state-of-the-art mechanisms.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Name of the Parameters** & **Value** \\ \hline Network type & Wired, wireless \\ Simulation time & 5–20 min \\ Underlying transport layer & Transmission Control Protocol (TCP) \\ Bandwidth in wired line & 1 Gbps \\ Bandwidth in wireless line & 1, 2, 5.5, 11 Mbps \\ eNB’s power & 46 dBm \\ Delay & 2 ms \\ Packet size & 8.2, 8 KB \\ File size & 8.2 KB, 1 MB, 4.1 MB \\ \hline \hline \end{tabular}
\end{table}
Table 2: Simulation parameters.  
The performances of the hash caching, proposed cluster-based and state-of-the-art caching mechanisms are shown in Figure 10 in terms of content delivery time. We already described the problem and the solution of hash caching in Figures 7 and 8. We considered the same simulation scenario for all the caching mechanisms. The simulation result shows that our proposed cluster-based mechanism needs less time than the hash caching mechanism but similar to the state-of-the-art caching mechanisms. Although the state-of-the-art caching mechanisms need equal time compared to our proposed mechanism, the drawbacks of LCE and LCD do not motivate to be used in the real network environment. The cluster-based approach provides better results in hash caching and on-path caching mechanism due to our proposed efficient cache replacement mechanism in the cluster-based network environment.