# Multi-Device to Multi-Device (MD2 MD) Content-Centric Networking Based on Multi-RAT Device
## 1 Introduction  
With the spread of smartphones and tablet PCs, the volume of mobile traffic has been rapidly increasing, year upon year. The majority of mobile traffic is in video format. Video traffic already accounts for 55% of all mobile traffic, and this is expected to exceed 70% in 2016 [1]. In addition, video traffic should be afforded the greatest consideration in a mobile communications network because it uses much more data than either text or audio. By using a smartphone or a tablet PC, users are able to access video services such as VOD and YouTube while on the move. In other words, users have become able to use large amounts of data at any time, and anywhere. As a result, the mobile network has become overloaded. To solve the problem of the overloading of base stations, device-to-device (D2D) communication has been attracting attention. D2D communication is a technique whereby devices communicate directly, without going through the network infrastructure [1; 2]. Some of the main application services using D2D are Machine-to-Machine (M2M), Internet of Things (IoT), and Cyber-Physical-System (CPS). In particular, it is possible to avoid increasing the load on the Core network because the communication between the devices (located in a certain area) is the main traffic, such as when Smart Factory, Smart Farm, or enterprise/campus Intranet through M2M is used [3]. As a major advantage of using D2D technology in a mobile network, D2D communications bring significant improvements of spectral efficiency by underlaying cellular networks. D2D communication enables users in proximity to exchange information directly, without traversing to the base stations or core network in two hops, and it has attracted increasing attention from both industrial and academic communities. Due to the potential proximity gain, reuse gain, and hop gain, D2D communication can significantly increase system spectral efficiency and energy efficiency and, as such, has been considered a promising candidate technique for nextgeneration cellular networks. Accordingly, many studies have focused on a D2D communications scheme that underlays the cellular network infrastructure in order to increase the cellular capacity, improving the users' throughput, and extending the battery lifetime of user equipment. However, most conventional D2D-related works are limited to physical layer problems such as spectrum sharing and channel interference [4]. In the meantime, network security technologies based on distributed processing and Peer-to-Peer (P2P) concepts are emerging, and it is necessary to study the higher layers, beyond the research centered on the physical layer [5]. D2D communication can be divided into cellular-network-based D2D communication and autonomous D2D communication. Autonomous D2D communication has attracted considerable attention due to its ability to operate in situations where the cellular network has failed, such as in the wake of a natural disaster. Also, existing IP-based host-centric network structures incur the problem of bottlenecks caused by the inefficiency of requests and the distribution of content such as video. For these reasons, current network structures cannot handle the trend towards large-volume content. Accordingly, studies of the Internet of the future, which will have to overcome the fundamental limitations of the current Internet structure, have been actively promoted [6]. Content-centric networking (CCN) is one area that Internet-related research will address in the future [7]. CCN is a communication protocol that supports routing and caching based on content names. CCN is suitable for an IoT environment since it can reduce the complexity of the autoconfiguration mechanism, relative to the approach based on the layered protocol stack [8; 9; 10; 11]. Currently, the IoT is mostly related to sensor control, in which small amounts of data, such as sensor values, are communicated to and from a fixed device, such as a sensor.