# An NDN Cache Management for MEC
## 6 Conclusions  
Since NDN utilizes the in-network caches of content, a cache management scheme is an essential technology of NDN. So far, most cache management schemes cache transmitted content in RsENs. Because of this, such an approach would make it possible to reduce the amount of network traffic that is exchanged between core networks. Such an approach assumes that the content's popularity is related to how frequently it is requested. However, many reports have shown that the usage rate of most content shared through the Internet is low. Hence, although content has been cached on nodes, it can happen that the caches of the content are not used at all. Therefore, existing CMSs for NDN can waste the cache storage of a node but do not significantly improve network efficiency. Practically, when we analyze both the _Interest/Data_ traffic flow of NDN and the cache usage rate of each node, we find that some caches are not utilized at all. Also, we find that _Data_ that is cached in the requestor- side networks has a lower hit rate than _Data_ that is cached in the provider-side network.  
Hence, we propose to consider simultaneously two decision factors, both a content popularity and the cache hit rate of each node, when NDN selects nodes to cache transmitted _Data_. Also, to prove the effectiveness of our proposal, we suggest a simple cache model using our proposal and evaluate the performance of the model. Since this proposed scheme caches _Data_ on nodes with high cache hit rates, it enhances the cache-storage efficiency by up to 65% compared with existing cache management schemes in which the content is cached both in the requestor-side network and in the provider-side network without degrading the network efficiency. That is, LdC improves the storage overheads of nodes without degradation of transmission performance.  
The main contribution of this work consists of three points: First, we showed that the cache hit rate of a node is an important factor as much as the popularity of content. When NDN considers these two factors simultaneously, it can improve the storage overheads of nodes.  
Second, when implementing MEC for caching content in edge networks, it is necessary to consider the case where caches in edge networks are not used at all. Hence, it should be needed to design a special cache management scheme for requestor-side network domain.  
Finally, we suggest a future work which sets the cache lifetime of each node considering these two factors. CMS generally considers the lifetime of caches. However, most CMSs take a formalized rule and use a fixed value. Using these two factors, it may be possible to generate a flexible lifetime of caches.  
Conceptualization, D.K. and J.L.; methodology, D.K.; software, D.K.; validation, D.K. and J.L.; formal analysis, D.K.; investigation, D.K.; resources, D.K.; data curation, D.K.; writing--original draft preparation, D.K.; writing--review and editing, J.L.; visualization, J.L.; supervision, D.K.; project administration, D.K.; and funding acquisition, D.K. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1B03034215 and 2016R1D1A1B03931628).  
The authors declare no conflict of interest.