In this section, we will outline trial experiences, often conducted within collaborative project efforts. Our focus here is on the realization of the various deployment configurations identified in
Section 4; therefore, we categorize the trial experiences according to these deployment configurations. While a large body of work exists at the simulation or emulation level, we specifically exclude these studies from our analysis to retain the focus on real-life experiences.
Although the FP7 PURSUIT [
IEEE_Communications] efforts were generally positioned as a Clean-slate ICN replacement of IP (
Section 4.1), the project realized its experimental testbed as an L2 VPN-based overlay between several European, US, and Asian sites, following the overlay deployment configuration presented in
Section 4.2. Software-based forwarders were utilized for the ICN message exchange, while native ICN applications (e.g., for video transmissions) were showcased. At the height of the project efforts, about 70+ nodes were active in the (overlay) network with presentations given at several conferences, as well as to the ICNRG.
The Network of Information (NetInf) is the approach to ICN developed by the EU FP7 Scalable and Adaptive Internet Solutions (SAIL) project [
SAIL]. NetInf provides both name-based forwarding with CCNx-like semantics and name resolution (for indirection and late binding). The NetInf architecture supports different deployment options through its convergence layer, such as using UDP, HTTP, and even DTN underlays. In its first prototypes and trials, NetInf was deployed mostly in an HTTP embedding and in a UDP overlay following the overlay deployment configuration in
Section 4.2. [
SAIL_Prototyping] describes several trials, including a stadium environment and a multi-site testbed, leveraging NetInf's routing hint approach for routing scalability [
SAIL_Content_Delivery].
The Named Data Networking (NDN) is one of the research projects of the National Science Foundation (NSF) of the USA as part of the Future Internet Architecture (FIA) Program. The original NDN proposal was positioned as a Clean-slate ICN replacement of IP (
Section 4.1). However, in several trials, NDN generally follows the overlay deployment configuration of
Section 4.2 to connect institutions over the public Internet across several continents. The use cases covered in the trials include real-time videoconferencing, geolocating, and interfacing to consumer applications. Typical trials involve up to 100 NDN-enabled nodes [
NDN-testbed] [
Jangam].
ICN2020 is an ICN-related project of the EU H2020 research program and NICT [
ICN2020-overview]. ICN2020 has a specific focus to advance ICN towards real-world deployments through applications, such as video delivery, interactive videos, and social networks. The federated testbed spans the USA, Europe, and Japan. Both NDN and CCNx approaches are within the scope of the project.
ICN2020 has released a set of interim public technical reports. The report [
ICN2020-Experiments] contains a detailed description of the progress made in both local testbeds and federated testbeds. The plan for the federated testbed includes integrating the NDN testbed, the CUTEi testbed [
RFC 7945] [
CUTEi], and the GEANT testbed [
GEANT] to create an overlay deployment configuration of
Section 4.2 over the public Internet. The total network contains 37 nodes. Since video was an important application, typical throughput was measured in certain scenarios and found to be in the order of 70 Mbps per node.
UMOBILE is another of the ICN research projects under the H2020 research program [
UMOBILE-overview]. The UMOBILE architecture integrates the principles of DTN and ICN in a common framework to support edge computing and mobile opportunistic wireless environments (e.g., post-disaster scenarios and remote areas). The UMOBILE architecture [
UMOBILE-2] was developed on top of the NDN framework by following the overlay deployment configuration of
Section 4.2. UMOBILE aims to extend Internet functionally by combining ICN and DTN technologies.
One of the key aspects of UMOBILE was the extension of the NDN framework to locate network services (e.g., mobility management and intermittent connectivity support) and user services (e.g., pervasive content management) as close as possible to the end users to optimize bandwidth utilization and resource management. Another aspect was the evolution of the NDN framework to operate in challenging wireless networks, namely in emergency scenarios [
UMOBILE-3] and environments with intermittent connectivity. To achieve this, the NDN framework was leveraged with a new messaging application called Oi! [
UMOBILE-4] [
UMOBILE-5], which supports intermittent wireless networking. UMOBILE also implements a new data-centric wireless routing protocol, DABBER [
UMOBILE-6] [
DABBER], which was designed based on data reachability metrics that take availability of adjacent wireless nodes and different data sources into consideration. The contextual awareness of the wireless network operation is obtained via a machine-learning agent running within the wireless nodes [
UMOBILE-7].
The consortium has completed several ICN deployment trials. In a post-disaster scenario trial [
UMOBILE-8], a special DTN face was created to provide reachability to remote areas where there is no typical Internet connection. Another trial was the ICN deployment over the "Guifi.net" community network in the Barcelona region. This trial focused on the evaluation of an ICN edge computing platform, called PiCasso [
UMOBILE-9]. In this trial, ten (10) Raspberry Pis were deployed across Barcelona to create an ICN overlay network on top of the existing IP routing protocol (e.g., qMp routing). This trial showed that ICN can play a key role in improving data delivery QoS and reducing the traffic in intermittent connectivity environments (e.g., wireless community network). A third trial in Italy was focused on displaying the capability of the UMOBILE architecture to reach disconnected areas and assist responsible authorities in emergencies, corresponding to an infrastructure scenario. The demonstration encompassed seven (7) end-user devices, one (1) access point, and one (1) gateway.
POINT and RIFE are two more ICN-related research projects of the H2020 research program. The efforts in the H2020 POINT and RIFE projects follow the underlay deployment configuration in
Section 4.3.2; edge-based NAPs provide the IP/HTTP-level protocol mapping onto ICN protocol exchanges, while the SDN underlay (or the VPN-based L2 underlay) is used as a transport network.
The multicast and service endpoint surrogate benefit in HTTP-based scenarios, such as for HTTP-level streaming video delivery, and have been demonstrated in the deployed POINT testbed with 80+ nodes being utilized. Demonstrations of this capability have been given to the ICNRG, and public demonstrations were also provided at events [
MWC_Demo]. The trial has also been accepted by the ETSI MEC group as a public proof-of-concept demonstration.
While the aforementioned demonstrations all use the overlay deployment, H2020 also has performed ICN underlay trials. One such trial involved commercial end users located in the PrimeTel network in Cyprus with the use case centered on IPTV and HLS video dissemination. Another trial was performed over the "Guifi.net" community network in the Barcelona region, where the solution was deployed in 40 households, providing general Internet connectivity to the residents. Standard IPTV Set-Top Boxes(STBs), as well as HLS video players, were utilized in accordance with the aim of this deployment configuration, namely to provide application and service migration.
The H2020 Facility for Large-Scale Adaptive Media Experimentation (FLAME) efforts concentrate on providing an experimental ground for the aforementioned POINT/RIFE solution in initially two city-scale locations, namely in Bristol and Barcelona. This trial followed the underlay deployment configuration in
Section 4.3.2, as per the POINT/RIFE approach. Experiments were conducted with the city/university joint venture Bristol-is-Open (BIO) to ensure the readiness of the city-scale SDN transport network for such experiments. Another trial was for the ETSI MEC PoC. This trial showcased operational benefits provided by the ICN underlay for the scenario of a location-based game. These benefits aim at reduced network utilization through improved video delivery performance (multicast of all captured videos to the service surrogates deployed in the city at six locations), as well as reduced latency through the play out of the video originating from the local NAP, collocated with the Wi-Fi Access Point (AP) instead of a remote server, i.e., the playout latency was bounded by the maximum single-hop latency.
Twenty three (23) large-scale media service experiments are planned as part of the H2020 FLAME efforts in the area of Future Media Internet (FMI). The platform, which includes the ICN capabilities, integrated with NFV and SDN capabilities of the infrastructure. The ultimate goal of these platform efforts is the full integration of ICN into the overall media function platform for the provisioning of advanced (media-centric) Internet services.
The CableLabs ICN work reported in [
White] proposes an underlay deployment configuration based on
Section 4.3.2. The use case is ICN for content distribution within complex CDN server farms to leverage ICN's superior in-network caching properties. This CDN based on "island of ICN" is then used to service standard HTTP/IP-based content retrieval requests coming from the general Internet. This approach acknowledges that whole scale replacement (see
Section 4.1) of existing HTTP/IP end-user applications and related web infrastructure is a difficult proposition. [
White] is clear that the architecture proposed has not yet been tested experimentally but that implementations are in process and expected in the 3-5 year time frame.
[
Baccelli] summarizes the trial of an NDN system adapted specifically for a wireless IoT scenario. The trial was run with 60 nodes distributed over several multistory buildings in a university campus environment. The NDN protocols were optimized to run directly over 6LoWPAN wireless link layers. The performance of the NDN-based IoT system was then compared to an equivalent system running standard IP-based IoT protocols. It was found that the NDN-based IoT system was superior in several respects, including in terms of energy consumption and for RAM and ROM footprints [
Baccelli] [
Anastasiades]. For example, the binary file size reductions for NDN protocol stack versus standard IP-based IoT protocol stack on given devices were up to 60% less for ROM size and up to 80% less for RAM size.
The National Research and Education Network (NREN) ICN Testbed is a project sponsored by Cisco, Internet2, and the US Research and Education community. Participants include universities and US federal government entities that connect via a nationwide VPN-based L2 underlay. The testbed uses the CCNx approach and is based on the [
CICN] open-source software. There are approximately 15 nodes spread across the USA that connect to the testbed. The project's current focus is to advance data-intensive science and network research by improving data movement, searchability, and accessibility.
The DOCTOR project is a French research project meaning "Deployment and Securisation of new Functionalities in Virtualized Networking Environments". The project aims to run NDN over virtualized NFV infrastructure [
Doctor] (based on Docker technology) and focuses on the NFV MANO aspects to build an operational NDN network focusing on important performance criteria, such as security, performance, and interoperability.
The data plane relies on an HTTP/NDN gateway [
Marchal] that processes HTTP traffic and transports it in an optimized way over NDN to benefit from the properties of the NDN island (i.e., by mapping HTTP semantics to NDN semantics within the NDN island). The testbed carries real Web traffic of users and has been currently evaluated with the top 1000 most popular websites. The users only need to set the gateway as the web proxy. The control plane relies on a central manager that uses machine-learning-based detection methods [
Mai-1] from the date gathered by distributed probes and applies orchestrated countermeasures against NDN attacks [
Nguyen-1] [
Nguyen-2] [
Mai-2] or performance issues. A remediation can be, for example, the scale up of a bottleneck component or the deployment of a security function, like a firewall or a signature verification module. Test results thus far have indicated that key attacks can be detected accurately. For example, content poisoning attacks can be detected at up to over 95% accuracy (with less than 0.01% false positives) [
Nguyen-3].
Hybrid ICN [
H-ICN_1] [
H-ICN_2] is an approach where the ICN names are mapped to IPv6 addresses and other ICN information is carried as payload inside the IP packet. This allows standard (ICN-unaware) IP routers to forward packets based on IPv6 info but enables ICN-aware routers to apply ICN semantics. The intent is to enable rapid hybrid deployments and seamless interconnection of IP and Hybrid ICN domains. Hybrid ICN uses [
CICN] open-source software. Initial tests have been done with 150 clients consuming DASH videos, which showed good scalability properties at the server side using the Hybrid ICN transport [
H-ICN_3] [
H-ICN_2].
In summary, there have been significant trials over the years with all the major ICN protocol flavors (e.g., CCNx, NDN, and POINT) using both the ICN-as-an-Overlay and ICN-as-an-Underlay deployment configurations. The major limitations of the trials include the fact that only a limited number of applications have been tested. However, the tested applications include both native ICN and existing IP-based applications (e.g., videoconferencing and IPTV). Another limitation of the trials is that all of them involve less than 1k users.
Huawei and China Unicom have just started trials of the ICN-as-a-Slice configuration to demonstrate ICN features of security, mobility, and bandwidth efficiency over a wired infrastructure using videoconferencing as the application scenario [
Chakraborti]; also, this prototype has been extended to demonstrate this over a 5G-NR access.
The Clean-slate ICN approach has obviously never been in trials, as complete replacement of Internet infrastructure (e.g., existing applications, TCP/IP protocol stack, IP routers, etc.) is no longer considered a viable alternative.
Finally, Hybrid ICN is a Composite-ICN approach that offers an interesting alternative, as it allows ICN semantics to be embedded in standard IPv6 packets so the packets can be routed through either IP routers or Hybrid ICN routers. Note that some other trials, such as the DOCTOR testbed (
Section 6.2.6), could also be characterized as a Composite-ICN approach, because it contains both ICN gateways (as in ICN-as-an-Underlay) and virtualized infrastructure (as in ICN-as-a-Slice). However, for the DOCTOR testbed, we have chosen to characterize it as an ICN-as-an-Underlay configuration because that is a dominant characteristic.