# Joint Location-Dependent Pricing and Request Mapping in ICN-Based Telco CDNs For 5G
## 1 Introduction  
Content delivery networks (CDNs) have become indispensable for data dissemination on the Internet. By employing caches that are proximal to end users, CDNs provide low-latency and better data availability, increasing the quality of experience (QoE). According to the Cisco Visual Networking Index, CDNs will carry 72% of Internet traffic by 2022, up from 56% in 2017 [1]. With the continuous growing requirements of bandwidth-hungry and latency-sensitive applications such as 8K video and automatic driving, more and more CDN companies are deploying their CDN sites closer to end users, i.e., in access networks. In this trend, telecommunication companies/mobile network operators (MNOs) have more incentives and requirements than ever to deploy more CDN sites in their hierarchical cloudified networks [2; 3; 4]. On one hand, they are re-designing the network architecture to support better flexibility and higher efficiency by introducing software-defined networking (SDN) and network function virtualization (NFV) techniques. The re-designed architecture will help provide a better content delivery service at a lower cost (e.g., by saving bandwidth). On the other hand, the representative scenarios in the 5G era require rigorous latency and bandwidth guarantees, which cannot be satisfied by existing remote CDN sites alone. Thus, sites in access networks are needed. In addition, MNOs have a cost advantage over traditional CDN companies when providing CDN services in access networks. The reason is that MNOs are the owners of the access networks, thus theydo not have to pay for transit costs or leasing of servers. China Unicom has published its network cloudification plan in the 5G era [5] and proposed the cloud-edge-fog collaborative content-oriented CDN architecture called CUBE-CDN [6]. Compared with traditional CDNs, MNOs' CDN (called telco CDNs in the rest of the paper) in the 5G era faces two main forms of challenge. First, telco CDN should be operated in cooperation with the underlying network which evolves towards a content-oriented and information-centric architecture [7; 8]. This is because telco is the owner of both the overlay and the underlay, whose performance should be taken into account simultaneously. In the context of underlay architecture evolution, Information-centric networking (ICN) has attracted much attention. In ICN, every router is cache-enabled and protocols are designed to be in content-centric abstraction in contrast to today's host-centric abstraction. Communication is based on content look-up and content caching on the path of content delivery (i.e., on-path caching), enabling content-awareness at the network layer. Once a content is cached in a router, the requests of nearby users for this content can all be satisfied by this router directly without being directed to remote servers, thus the response latency is reduced. However, the cache space in routers is limited in comparison to the powerful caching capability of CDNs. In addition, routers that execute content look-up locally can hardly support line-speed forwarding [9]. On the other hand, CDNs accelerate content delivery by directing content requests to the most suitable CDN site, which is always outside (or at least some distance) from the network that the content requests come from (i.e., off-path caching). Telco CDNs enable edge caching in the access network by deploying a large number of edge sites consisting of caching servers with a high capacity. In this context, we argue that the benefits of both ICN and telco CDN can be utilized in an integrated design fashion, which has rarely been discussed before. Second, the distributed and cloudified infrastructure brings both flexibility and challenges in key CDN operational aspects. Existing works have focused on some of the challenges. In [10; 11], they raise the concept of CDN-as-a-service (CDNaaS), which enables on-demand customization of various CDN types with different service level agreements (SLAs).