# Request Expectation Index Based Cache Replacement Algorithm for Streaming Content Delivery over ICN
## 4 Simulations and Results
### Scenario 1: Hierarchical Topology with One Producer  
In this scenario, we evaluate the performance of the cache replacement algorithms in the 5-level complete binary tree topology. We implement one video streaming server connected to the root router as the black router shows in Figure 5a. Twenty-five video streaming files are supplied on this server, and each contains 1000 chunks that can be requested independently. Accordingly, the total chunk number is 25,000 items. With respect to the file-level popularity, studies have shown that it follows the Zipf distribution. Therefore, we implement 100 video viewers connected to the leaf routers, as represented by the white routers in Figure 5a, and the popularity of requests for different video files follows a Zipf distribution (\(\alpha\) = 0.8) [44]. In addition, these viewers request videos with given intervals that are assumed to follow the Exponential distribution with a mean of 1 s, that is, the time unit \(\delta t\) of the \(REQ_{f}(i)\) measurement is set to 1 s. Additionally, the viewer requests for a video following the order of the sequence number \(j\) from the beginning of the video, but may stop before the end of the video. According to the observations in study [41], a Pareto distribution (with the mean between 54% and 61% of the total video length) fits the measured viewer request duration. Therefore, we assume that the request duration of viewers follows the Pareto distribution with a mean of 57% of the video duration. The simulation is performed across a range of cache capacity from 200 chunks to 2000 chunks for each ICN node. The simulation results presented in Figure 6a,b show significant differences among the LRU, LFU, TLP-TTH and RXI-based algorithm. The average cache hit ratio and the average hop count are calculated among each ICN router with the router cache capacity ranging from 200 chunks to 2000 chunks. Compared with TLP-TTH, the average cache hit ratio is improved from 7.44% to 8.05% by the RXI-based algorithm, thus the average cache hit ratio increment is over 8%, while TLP-TTH shows an 11% increment over LFU. Therefore, the overall performance increment is approximately 20% for the RXI-based algorithm compared with LFU and 32% compared with LRU. The RXI-based algorithm shows a 1.1% decrement in average transfer distance compared with TLP-TTH and a nearly 3.3% decrement compared with LFU. The results above show that, compared with the reference algorithms, the RXI-based algorithm enhances the utilization of the cache space; thus, viewers can acquire video chunks from closer routers. In other words, the RXI-based algorithm lightens the pressure on the original video sources. The RXI-based algorithm reduces the total network traffic and the total retrieval time compared with LRU, LFU and TLP-TTH, as shown in Figure 6c,d. Because of the reduction in the average delivery distance between viewers and the target content chunks, the unnecessary network traffic among intermediate routers and the average retrieval time are reduced. These reductions are further intensified by the high cache hit ratio of the RXI-based algorithm. In conclusion, to deliver the same number of video chunks, the RXI-based algorithm consumes less network resources and requires less time than LRU, LFU and TLP-TTH, and when the cache size is limited (e.g., cache size \(<\) 1400 chunks), the improvement is more evident. The performance improvements are mainly due to the following facts. Fine-grained estimation of future request probability helps with the accurate prediction of future request behaviors, so that the underutilized cache capacity can be efficiently used.