# Performance Analysis of Cache Based on Popularity and Class in Named Data Network
## 1 Introduction  
The increase in a bit rate of multimedia traffic makes the TCP/IP architecture inefficient in delivering time-sensitive multimedia traffic. We need the content-based network instead of a host-based network [1]. Named Data Network (NDN) is a content-centric network that utilizes network resources to store data on routers [2]. The whole network resources need to support communication maximally. NDN allows consumers to find the data requested at the nearest router. This mechanism reduces the overall network load and potential delay. Furthermore, the placement of content at a certain node that is closer to the consumer causes communication to be more efficient, while router nodes independently place content in its content store without coordinating with others on the network. This mechanism also makes NDN strongly support consumer mobility with content requests based on the name, and not on a specific host address [2, 3]. The network responds to a consumer request in the aggregate, and it makes communication more efficient. Nowadays, communication occurs with some unique characteristics [4], such as consumers repeatedly asking for the same content from the server, the character is similar to the local environment, and dynamic changes in demand over time. The IP network has become inefficient because theconsumer is only served by the server, despite the distance. This system is called host-based communication. In the IP network, the consumers request content to a specific address. Therefore, a shift to the host-based paradigm into the content-based, namely Named Data Network (NDN), is needed because what is needed by the consumer is content, not the server. NDN makes the process of sending data more efficient than IP networks because, it allows consumers to transfer interest packets to the system, and not to a specific IP address [5; 6]. NDN routers can store data/content in its content store, and when an interest packet containing the consumer's request enters an NDN router, it checks whether the requested content exists on its content store. When the router has the requested data, it immediately sends a copy to the consumer, and when it does not, it checks the Pending Interest Table (PIT). When the PIT has no information on the requested data, the router adds this request information and the information of the sending side. The request is therefore forwarded to the next router using the information in the Forwarding Information Base (FIB) until it identifies the desired content. One of the essential components of the NDN router with a limited resource is the content store. Therefore, a caching mechanism capable of optimizing the content stores is needed by considering the difference in traffic character on the network. The size of the content store [7] and the cache policy [8] affect the system performance. Several studies have been conducted on energy consumption [9; 10]. [PERSON] et al. explained that research on the caching mechanism in NDN that distinguishes content treatment for different services is vital [11]. [PERSON] et al. researched the differentiation of service classes on NDN. These studies discussed differentiating service classes on IP, such as DiffServ, which is adjusted and used in NDN [12]. In this scheme, content groups have been distinguished with differing interest packet's marking rate depending on the class, without special treatment on the cache. Furthermore, differentiation of package treatment is carried out on its forwarding activities. [PERSON] et al. [13] stated that the difference in the treatment of data is carried out by statically and manually distinguishing its lifetime for each class. [PERSON] et al. carried out a research that formulated caching placement into optimizing problem in accordance with the imbalance of caching gain caused by different content popularity [14]. [PERSON] et al. further proposed a scheme regarding interdomain traffic saving and weighted hop saving. [PERSON] et al. [15] conducted research on the content store settings for different applications.