# Insights from the Experimentation of Named Data Networks in Mobile Wireless Environments
## 2 Related Work  
In the literature one can find several works on the deployment of solutions based on the ICN architecture, but a small number addresses large-scale infrastructures [5]. In this section, we overview the most relevant related works focused on the experimentation of ICN and NDN architectures in testbeds. [PERSON] et al. [2; 6; 7] introduced in 2009 the Content-Centered Network (CCN), a communication architecture built on named data, and compared it with an IP-based networks. In their comparison, several metrics were considered such as data transfer efficiency, content delivery efficiency, and Voice-over-CCN. Still, the scenario in use was a small controlled testbed in a laboratory environment. In [8], the authors discuss the comparison between the content Cache-supported NDN architecture cloudlets with location-oriented TCP/IP architecture. The work considers the placement of cloudlets at the edge of an NDN network, close to end users. They used a virtual tour guide that provides audio and visual content to tourists in popular locations as an application scenario. However, the testbed, consisting of a standard Dell Ubuntu 16.04 laptop to host the NDN cloudlet server and five Android phones as clients, seems very simple being far from representing a city's communications infrastructure, without considering any multi-radio access technology. In [9], the authors have repeated the experiments in [6] on a more complex communications infrastructure. They interconnect through the Internet some Consumers and a router to a Producer that is placed geographically far. They deploy the CCN over UDP to establish the connection between the two environments (CCN and Internet). The results are similar to those obtained by [6]. The solution proposed in [10], the Named-data Link State Routing protocol (NLSR), is a protocol for intra-domain routing in NDN. The NLSR, an application level protocol similar to many IP routing protocols, uses NDN's Interest/Data packets to disseminate routing updates over network. The authors made an evaluation in terms of CPU processing time, routing convergence time, and forwarding plane performance using Mini-NDN, an emulation tool based on Mininet. In [11] the authors propose and evaluate a scalable framework for lightweight authentication and hierarchical routing in NDN IoT. They demonstrate the scalability of their solution in a simulated dense environment with up to 40,000 nodes/km\({}^{2}\) whose results show an average onboarding convergence time of around 250 s and overhead of less than 20 kibibytes per node. However, they do not test their solution in a real environment. In [12], the authors present NDN as a solution for in-vehicle communication. The solution was deployed on an emulated automotive testbed of Raspberry PIs with Controller Area Network (CAN) interfaces and tests were performed using network traces datasets. In the same direction, the work in [13] discussed a comparative simulation-based study of these NDN deployments over Wi-Fi 6 for Internet-of-Vehicles using real vehicular traces. Both papers do not present a real NDN deployment. The work in [14] presents an NDN solution over ZigBee that evaluated, through three different scenarios, the suitability and ease of use of NDN in the IoT context. They compared their NDN implementation over ZigBee to the basic wireless NDN over Wi-Fi communication that uses the UDP/IP protocol stack to send NDN packets. In their tests, they tried different sets of Interest exchange rates and data packet sizes. They have measured the total time spent by each exchange (from sending the Interest to receiving the data) and also the ratio of Interests satisfied in each pool. Such tests were performed in controlled environments far from what is expected in a real smart city infrastructure. There are some solutions for the well-known multiplication of interest and data packets in NDN networks over Wi-Fi. In [15], the authors proposed an Access Point-based proxy of Interest mechanism to mitigate WLAN channel competition.