# Time Segmentation-Based Hybrid Caching in 5G-ICN Bearer Network
## 2 Related Work
### 5G-ICN Cache Technology  
Literature [11] divides content placement strategies into two main categories: (1) vertical management, which tends to choose the best content cache location to meet well-defined application scenarios; and (2) horizontal management, which tends to push popular content to the edge network to meet as many users as possible. Vertical management can be divided into three categories: centralized, distributed, and collaborative. In the centralized caching scheme, the controller entity or the server is used as the necessary network element to determine the cache location. Classic centralized schemes include ProbCache [17] and Random [18]. In the past three years, there have been many excellent centralized schemes proposed, such as BEP [19] and PPCs [20]. BEP is an improvement on the traditional intermediary strategy. PPCS is a progressive popular aware caching scheme. Nodes use local factors and metrics to determine content caching, which improves network efficiency by reducing the exchange of information between nodes. Classic distributed cache placement strategies include LCE [21], LCD [22], EC [23], and betweenness [24]. In recent years, some distributed caching schemes have also been proposed, such as MAGIC [25], Greedy Cache [26], and SDC [27; 28]. In the collaborative scheme, nodes in the communication path can establish cooperation and exchange information with each other to explore more functions and better use network resources. The classic caching mechanism is WAVE [29]. In recent years, collaborative caching technology has also been studied and developed, such as GAC [30], COD [31], and other strategies. GAC is a gain aware two round cooperative caching scheme, which reduces data redundancy in the network while enhancing content diversity. COD is a cooperative on-demand caching strategy. COD tends to reduce the number of nodes that cache content in the network. In the strategy of horizontal managements, paper [32] proposes an edge cache architecture for 5g-icn networks, which aims to improve cache performance in global edge networks. The main idea is to achieve a compromise between the computing cost and cache revenue. Paper [33] proposed an intelligent caching heuristic algorithm to mine the central effect of consumer behavior to extract consumer content preferences in each slot. Paper [34] proposed a caching strategy based on user group interest preferences. Paper [35] proposed an analysis framework based on ICN edge caching scheme. Figure 1: 5G-ICN network architecture. Besides, paper [36] points out that the existing caching strategy in CCN wired networks will not be able to meet the needs of mobile CCN network caching because it does not consider user mobility, so a caching strategy suitable for mobile CCN networks is proposed. The author uses a semi-Markov model to model user mobility, establishes a mathematical model between user mobility and content popularity, and uses a multiple linear regression model to predict the popularity of the next time for caching. Paper [16] proposes an ICN-enabled RAN architecture for 5G edge computing environments. The base station provides device-to-device communication and ICN application layer support. The author also sets thresholds based on content popularity and provides a content prefetching strategy based on ICN naming. NRS plays an important role in ICN cache. NRS is mainly used to establish, maintain, and publish the mapping relationship between the information name and the address of the information or the information provider, and provide a fast name resolution function [37]. The Host Name and Identifier System (HNIS) [38] developed for 5G-ICN adopts an ID/LOC separation architecture. It is used for hostname and identifier mapping, which is suitable for 5G networks and emerging network architectures. HNIS designs a corresponding name registration and resolution mechanism, and realizes cross-domain mobile resolution through the dynamic binding of names to global location identifiers and local location identifiers.