# An NDN Cache Management for MEC
## 1 Introduction  
Since P2P networking technology was first introduced, it has become the general approach of advanced network technologies to use caches (i.e., replica of data), which saves multiple nodes. One of the main characteristics of such technologies is to shift the networking paradigm from 'host-centric networking' to 'content-centric networking' [1; 2; 3]. When using in-network caches, data-providers can expect that other nodes can handle most request-packets and users can seamlessly retrieve requested data regardless of the network and system state of the data-providers. Hence, it appears very attractive to utilize caches from the viewpoints of users and data-providers.  
The named data networking architecture (NDN), which is a one information centric networking architecture (ICN), caches a data-packet (_Data_) in the network-nodes on a downstream network path of the _Data_. When a node receives a request-packet (_Interest_) for the _Data_, if the node has cached the _Data_, it directly transmits the cached _Data_ to requesters as a response. Since one of the intermediate nodes on an upstream network path of _Interest_ can directly respond to the _Interest_, a user can receive theData_ more rapidly. Hence, NDN is considered as one of alternative solutions to efficiently implement mobile edge computing [4].  
Theoretically, NDN is designed to cache _Data_ on all nodes of a downstream network path of the _Data_. However, considering the amount of data that is transmitted through networks today, it must be assumed that each network-node requires huge storage space. Additionally, if each network-node on the upstream network path of _Interest_ tries to search the relevant _Data_ in its huge storage, it can cause serious service-delays. Therefore, various cache management schemes have been presented to improve this inefficiency of NDN [5; 6; 7; 8; 9; 10].  
The cache management scheme (CMS) generally tries to reduce unnecessary cache redundancy and to improve transmission overheads for transmitting _Data_. To do this, many CMSs utilize common approaches as follows:  
* To gradually increase the number of nodes caching _Data_ proportionally to the request frequency of the _Data_.
* To cache _Data_ as near a requester-side edge network (RsEN) as possible.  
In particular, the latter approach expects that _Interest_ generated in RsEN can be responded by nodes in the RsEN without transmitting the _Interest_ to the core network. To do this, it should be assumed that'many' nodes of'many' RsENs have cached relevant _Data_. However, it would not be a practical assumption because most content objects are not as popular as expected. For example, the average usage ratio of YouTube content does not exceed 0.01%. Such an analysis leads to two facts:  
* Many _Interests_ that are generated in RsENs can be transmitted to the original content providers.
* Even if _Data_ is cached in several RsENs, except for a few famous content objects, the caches of most _Data_ cannot be used at all. Therefore, such caches can just waste the storage of nodes.  
In this paper, to improve the storage overheads of existing CMS, we propose an improved scheme considering two factors at the same time as follows:  
* The popularity of the _Data_. As existing CMSs, we also gradually increase the number of nodes caching _Data_ proportionally to the generation frequency of the _Interests_ requesting the _Data_.
* The cache usage rate of each node. We first analyze the cache hit rate of nodes. Then, we select nodes such that the cache hit frequency of these nodes is relatively high.  
When applying these factors, this proposed scheme can enhance the storage efficiency of nodes up to 65% compared with existing CMSs without degrading the network efficiency.