# Time Segmentation-Based Hybrid Caching in 5G-ICN Bearer Network
## 3 Path Segmentation-Based Hybrid Caching
### Caching in Low Liquidity Period
Node cache hit ratio refers to the ratio of content requests cached by nodes to the total number of requests arriving at nodes. In this paper, we calculate the overall average cache hit ratio. Next, we will conduct comparative simulation from two aspects. The first is to fix the mobile rate of users in the high liquidity period, gradually increase the content popularity from 0.6 to 1.2, and observe the network performance of our scheme. The second is to set the content popularity to 0.8, gradually increase the user mobility rate in high circulation periods from 100 to 1000, and observe the stability of our caching scheme in terms of cache hit rate and latency in this process. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Cache Replacement Policy & LFU \\ Number of contents & \(10^{5}\) \\ Requests number for system warm-up & \(10^{4}\) \\ Total mobile user requests & \(10^{4}\) \\ Ratio of the cache space to the total content size & 0.04 \\ User movement rate in high liquidity period & [100, 200, 400, 600, 800, 1000]. \\ User movement rate in low liquidity period & 10 \\ skewness (\(\alpha\)) & [0.6, 0.7, 0.8, 0.9, 1.0, 1.2] \\ Experiment run time for each scenario & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experiment parameters. Figure 5: Simulation topologies. #### 4.2.1 Impact of Skewness

We change the skewness \((\alpha)\) to observe the impact of the two network topologies on cache hit ratio and average latency. In this part of the experiment, the user movement rate is set to 400 in the high liquidity period. The results are shown in Figure 6. Greater skewness means that users have more requests for popular content. In both network topologies, ProbCache evaluates the remaining cache space and caches content request and return paths based on probability. In high liquidity period, users requesting content have the feature of frequent movement, which results in poor performance. CL4M triggers only once, so the contents of the cache are cached first at the node with the largest centrality, which not only results in uneven replica storage, but also in greater latency and lower hit rates. LCD and LCE show similar performance. In low liquidity period, users no longer switch 5G base stations frequently. Because LCD has the feature of keeping content as close to the edge of the network as possible, it should have a better advantage for users who are also on the edge of the network. However, in high liquidity period, active users will move to different base stations in a short period of time, and the latency of LCD will be affected. Our PSBC scheme clearly performs best. The results show that with the increasing skewness\((\alpha)\) of content, hits and latencies in all scenarios have been improved, but PSBC has maintained its lead: The average access latency of TSBC is lower than that of the other four cache strategies, and the hit ratio is higher than that of the other four cache strategies. This is because in dealing with the cross-transformation between high and low liquidity, we consider the movement rates of different users and divide the user traffic into periods. The diversity and richness of cache contents are given priority in the high liquidity period, which increases the content categories within the network and reduces the delay of content requests to the external network. Users need the popularity and freshness of content during low liquidity period, therefore the calculation of the cache value using the aforementioned parameters might increase the hit rate. Figure 6: Cache performance with different skewness. #### 4.2.2 Impact of Mobile User Rate

We changed the user movement rate during the high liquidity period to see the impact of the two network topologies on cache hit rates and latencies. In this part, skewness \((\alpha)\) is 0.8. The result is shown in Figure 7. In both network topologies, we can see the poor performance of ProbCache, which has the lowest hit rate and the highest latency.