Information-centric networking (ICN) provides low-latency content delivery with in-network caching, but delivery latency depends on cache distance from consumers. To reduce delivery latency, a scheme to cluster domains and retain the main popular content in each cluster with a cache distribution range has been proposed, which enables consumers to retrieve content from neighboring clusters/caches. However, when the distribution of content popularity changes, all content caches may not be distributed adequately in a cluster, so consumers cannot retrieve them from nearby caches. We therefore propose a dynamic clustering scheme to adjust the cache distribution range in accordance with the change in content popularity and evaluate the effectiveness of the proposed scheme through simulation.

Information-Centric Networking (ICN) is an innovative technology that provides low-loss, low-latency, high-throughput, and high-reliability communications for diversified and advanced services and applications. In this article, we present a technical survey of ICN functionalities such as in-network caching, routing, transport, and security mechanisms, as well as recent research findings. We focus on CCNx, which is a prominent ICN protocol whose message types are defined by the Internet Research Task Force. To facilitate the development of functional code and encourage application deployment, we introduce an open-source software platform called Cefore that facilitates CCNx-based communications. Cefore consists of networking components such as packet forwarding and in-network caching daemons, and it provides APIs and a Python wrapper program that enables users to easily develop CCNx applications for on Cefore. We introduce a Mininet-based Cefore emulator and lightweight Docker containers for running CCNx experiments on Cefore. In addition to exploring ICN features and implementations, we also consider promising research directions for further innovation.

Information-Centric Networking (ICN) originally innovated for efficient data distribution, is currently discussed to be applied to edge computing environment. In this paper, we focus on a more flexible context, in-network computing, which is enabled by ICN architecture. In ICN-based in-network computing, a function chaining (routing) method for chaining multiple functions located at different routers widely distributed in the network is required. Our proposal is a twofold approach, On-demand Routing for Responsive Route (OR3) and Route Records (RR). OR3 efficiently chains data and multiple functions compared with an existing routing method. RR reactively stores routing information to reduce communication/computing overhead. In this paper, we conducted a mathematical analytics in order to verify the correctness of the proposed routing algorithm. Moreover, we investigate applicabilities of OR3/RR to an edge computing context in the future Beyond 5G/6G era, in which rich computing resources are provided by mobile nodes thanks to the cutting-edge mobile device technologies. In the mobile environments, the optimum from viewpoint of “routing” is largely different from the stable wired environment. We address this challenging issue and newly propose protocol enhancements for OR3 by considering node mobility. Evaluation results reveal that mobility-enhanced OR3 can discover stable paths for function chaining to enable more reliable ICN-based in-network computing under the highly-dynamic network environment.

In human-computer interaction, acoustic scene classification (ASC) is one of the relevant research domains. In real life, the recorded audio may include a lot of noise and quiet clips, making it hard for earlier ASC-based research to isolate the crucial scene information in sound. Furthermore, scene information may be scattered across numerous audio frames; hence, selecting scene-related frames is crucial for ASC. In this context, an integrated convolutional neural network with a fusion attention mechanism (ICNN-FA) is proposed for ASC. Firstly, segmented mel-spectrograms as the input of ICNN can assist the model in learning the short-term time-frequency correlation information. Then, the designed ICNN model is employed to learn these segment-level features. In addition, the proposed global attention layer may gather global information by integrating these segment features. Finally, the developed fusion attention layer is utilized to fuse all segment-level features while the classifier classifies various situations. Experimental findings using ASC datasets from DCASE 2018 and 2019 indicate the efficacy of the suggested method.

This paper proposes a network tomography scheme for information-centric networking (ICN), which we call ICN tomography. When content is received over a conventional IP network, the communication occurs after converting the content name into an IP address, which is the locator, so as to identify the position of the network. By contrast, in ICN, communication is achieved by directly specifying the content name or content ID. The content is sent to the requesting user by a nearby node having the content or cache, making it difficult to apply a conventional network tomography that uses end-to-end quality of service (QoS) measurements and routing information between the source and destination node pairs as input to the ICN. This is because, in ICN, the end-to-end flow for an end host receiving some content can take various routes; therefore, the intermediate and source nodes can vary. In this paper, we first describe the technical challenges of applying network tomography to ICN. We then propose ICN tomography, where we use the content name as an endpoint to define an end-to-end QoS measurement and a routing matrix. In defining the routing matrix, we assume that the end-to-end flow follows a probabilistic routing. Finally, the effectiveness of the proposed method is evaluated through a numerical analysis and simulation.

In this paper, we focus on a large-scale ICN (Information-Centric Networking), and reveal the scaling property of ICN. Because of in-network content caching, ICN is a sort of cache networks and expected to be a promising architecture for replacing future Internet. To realize a global-scale (e.g., Internet-scale) ICN, it is crucial to understand the fundamental properties of such large-scale cache networks. However, the scaling property of ICN has not been well understood due to the lack of theoretical foundations and analysis methodologies. For answering research questions regarding the scaling property of ICN, we derive the cache hit probability at each router, the average content delivery delay of each entity, and the average content delivery delay of all entities over a content distribution tree comprised of a single repository (i.e., content provider), multiple routers, and multiple entities (i.e., content consumers). Through several numerical examples, we investigate the effect of the topology and the size of the content distribution tree and the cache size at routers on the average content delivery delay of all entities. Our findings include that the average content delivery delay of ICNs converges to a constant value if the cache size of routers are not small, which implies high scalability of ICNs, and that even when the network size would grow indefinitely, the average content delivery delay is upper-bounded by a constant value if routers in the network are provided with a fair amount of content caches.

Information-Centric or Content-Centric Networking (ICN/CCN) is a promising novel network architecture that naturally integrates in-network caching, multicast, and multipath capabilities, without relying on centralized application-specific servers. Software platforms are vital for researching ICN/CCN; however, existing platforms lack a focus on extensibility and lightweight implementation. In this paper, we introduce a newly developed software platform enabling CCN, named Cefore. In brief, Cefore is lightweight, with the ability to run even on top of a resource-constrained device, but is also easily extensible with arbitrary plugin libraries or external software implementations. For large-scale experiments, a network emulator (Cefore-Emu) and network simulator (Cefore-Sim) have also been developed for this platform. Both Cefore-Emu and Cefore-Sim support hybrid experimental environments that incorporate physical networks into the emulated/simulated networks. In this paper, we describe the design, specification, and usage of Cefore as well as Cefore-Emu and Cefore-Sim. We show performance evaluations of in-network caching and streaming on Cefore-Emu and content fetching on Cefore-Sim, verifying the salient features of the Cefore software platform.

Location-based forwarding is a key driver for location-based services. This paper designs forwarding information data structures for location-based forwarding in Internet Service Provider (ISP) scale networks based on Named Data Networking (NDN). Its important feature is a naming scheme which represents locations by leveraging space-filling curves.

Content-centric networking (CCN) promises efficient content delivery services with in-network caching. However, it cannot utilize cached chunks near users if they are not on the shortest path to the server, and it tends to mostly cache highly popular chunks in a domain. This degrades cache efficiency in obtaining various contents in CCN. Therefore, we propose hash-based cache distribution and search schemes to obtain various contents from nearby nodes and evaluate the effectiveness of this approach through simulation.

In order to support seamless mobility in the Information-Centric Networking (ICN) Architecture we propose the Named-Node Network Architecture (3NA). 3NA introduces two independent namespaces to ICN, the 3N namespace used to uniquely identify nodes within a network and the Point of Attachment (PoA) namespace to identify a node's PoA to the network. The mappings between the two namespaces, along with all the necessary mechanisms to keep the mappings updated over time, are used when routing ICN packets to improve delay and the goodput when either the producer or the consumer are mobile. To support simultaneous producer and consumer mobility, we expand on the 3NA by adding a new Protocol Data Unit (PDU), the DU PDU. The DU PDU permits the encapsulation of ICN packets in a header that has source and destination name fields which belong to 3NA's 3N namespace. The new PDU permits seamless connectivity as long as 3NA's point of attachment signaling is strictly followed. We demonstrate the performance of the DU PDU against our previous defined communication methods and Named Data Networking's (NDN) Smart Flooding forwarding strategy using our open source nnnSIM module for the ns-3 framework. The new PDU outperforms all existing alternatives when the producer or both consumer and provider are mobile, obtaining overall lower mean network delay and higher median goodput.

This paper looks at the history of research in the Technical Committee on Information Networks from the time of its inception to the present and provides an overview of the latest research in this area based on the topics discussed in recent meetings of the committee. It also presents possible future developments in the field of information networks.

The electron retention characteristics of memory capacitors with blocking oxide-silicon carbonitride (SiCN)-tunnel oxide stacked films were investigated for application in embedded charge trapping nonvolatile memories (NVMs). Long-term data retention in the SiCN memory capacitors was estimated to be more than 10 years at 85 °C. We presented an improved method to analyze the energy distribution of electron trap states numerically. Using the presented analytical method, electron trap states in the SiCN film were revealed to be distributed from 0.8 to 1.3 eV below the conduction band edge in the SiCN band gap. The presence of energetically deep trap states leads us to suggest that the SiCN dielectric films can be employed as the charge trapping film of embedded NVMs.

Energy efficiency is an important requirement to forth-coming NDN (Named Data Networking) networks and caching inherent to NDN is a main driver of energy reduction in such networks. This paper addresses the research question “Does caching really reduce the energy consumption of the entire network?”. To answer the question, we precisely estimate how caching reduces energy consumption of forth-coming commercial NDN networks by carefully considering configurations of NDN routers. This estimation reveals that energy reduction due to caching depends on energy-proportionality of NDN routers.

Information-centric networking (ICN) has been positioned for a number of years as a possible replacement to the IP-based Internet architecture with key promises in terms of network efficiency, privacy, security and novel applications. However, such wholesale replacement of the IP-based Internet through a new routing and service infrastructure has always been marred by the difficulties to gain adoption through existing stakeholders and market players, particularly solution providers. In this paper, we provide an evolutionary approach to introducing ICN in the real world by positioning an ICN-based solution as a routing-as-a-service offering for existing IP-based solutions. With this, we enable the expected benefits of ICN for the existing service and application basis of the current Internet. We will outline how we achieve this evolutionary introduction and how existing IP as well as HTTP-based services will be realized. An introduction into our gateway platform will be given, while also outlining first results from a recent showcase deployment.

As a research project supported jointly by the National Institute of Information and Communications Technology (NICT) in Japan and the European Commission under its 7th Framework Program, the GreenICN Project has been in operation from 2013 to 2016. The GreenICN project focused on two typical application scenarios, one a disaster scenario and the other a video delivery scenario. The disaster scenario assumed a situation of limited resources, and the video delivery scenario assumed a situation of large-scale content delivery. In both situations, the project challenged to provide “green”, i.e. energy-efficient, content delivery mechanism. For this goal, we designed an energy consumption model to lay out energy reduction policies. For the achievement of the policies, we improved ICN architecture, for example a name-based publish/subscribe mechanism, an effective cache management policy,energy-efficient security scheme and a new energy API. This paper provides a summary of our achievements and descriptions of some outcome.

In this work, we propose general, practical and accurate models to analyze the performance of multi-cache systems, in which a cache forwards its miss stream (i.e., requests which have not found the target item) to other caches. We extend a miss stream modeling technique originally known as Melazzi's approximation, which provides a simple but accurate approximate analysis for caches with cascade configurations. We consider several practical replication strategies, which have been commonly adopted in the context of ICN, taking into account the effects of temporal locality. Also, we capture the existing state correlations between neighboring caches by exploiting the cache eviction time. Our proposed models to handle traffic patterns allow us to go beyond the standard Poisson approximation under Independent Reference Model. Our results, validated against simulations, provide interesting insights into the performance of multi-cache systems with different replication strategies.

Named Data Networking (NDN) has emerged as an alternative to traditional IP-based networking for the achievement of Information-Centric Networking (ICN). Currently, most NDN is deployed over IP networks, but such an overlay deployment increases the transport network overhead due to the use of dual network control planes (NDN routing and IP routing). Software-Defined Networking (SDN) can be used to mitigate the network overhead by forwarding NDN packets without the use of IP routing. However, to deploy NDN over SDN, a variable NDN content name needs to be mapped to a fixed-size match field in an OpenFlow switch flow table. For efficient support of such a mapping task, we propose a new architecture that uses dual name for content: content name and Name Tag. The Name Tag is derived from the corresponding content name and is a legitimate IPv6 address. By using the proposed Name Tag, the SDN with an NDN control application can transport an IPv6 packet that encapsulates an NDN packet for an NDN name-based routing. We emulate the proposed architecture using Mininet and verify that it is feasible.

Enforcing access control policies in Information-Centric Networking (ICN) is difficult due to there being multiple copies of contents in various network locations. Traditional Access Control List (ACL)-based schemes are ill-suited for ICN, because all potential content distribution servers should have an identical access control policy or they should contact a centralized ACL server whenever their contents are accessed by consumers. To address these problems, we propose a distributed capability access control scheme for ICN. The proposed scheme is composed of an internal capability and an external capability. The former is included in the content and the latter is added to a request message sent from the consumer. The content distribution servers can validate the access right of the consumer through the internal and external capabilities without contacting access control policies. The proposed model also enhances the privacy of consumers by keeping the content name and consumer identification anonymous. The performance analysis and implementation show that the proposed scheme is feasible and more efficient than other access control schemes.

How to retrieve the closest content from an in-network cache is one of the most important issues in Information-Centric Networking (ICN). This paper proposes a novel content discovery scheme called Local Tree Hunting (LTH). By adding branch-cast functionality to a local tree for content requests to a Content-Centric Network (CCN) response node, the discovery area for caching nodes expands. Since the location of such a branch-casting node moves closer to the request node when the content is more widely cached, the discovery range, i.e. the branch size of the local tree, becomes smaller. Thus, the discovery area is autonomously adjusted depending on the content dissemination. With this feature, LTH is able to find the “almost true closest” caching node without checking all the caching nodes in the in-network cache. The performance analysis employed in Zipf's law content distribution model and which uses the Least Recently Used eviction rule shows the superiority of LTH with respect to identifying the almost exact closest cache.

This paper proposes a name-based routing mechanism called Routing Guidance Name (RGN) that offers new routing management functionalities within the basic characteristics of CCN. The proposed mechanism names each CCN router. Each router becomes a Data Provider for its name. When a CCN Interest specifies a router's name, it is forwarded to the target router according to the standard mechanism of CCN. Upon receiving an Interest, each router reacts to it according to RGN. This paper introduces a new type of node called a Scheduler which calculates the best routes based on link state information collected from routers. The scheduler performs its functions based on RGN. This paper discusses how the proposed system builds CCN FIB (Forwarding Information Base) in routers. The results of experiments reveal that RGN is more efficient than the standard CCN scheme. It is also shown that the proposal provides mobility support with short delay time. We explain a practical mobile scenario to illustrate the advantages of the proposal.