Content-Centric Networking (CCN) employs a hierarchical but location independent content naming scheme. While such a location independent naming brings various benefits including efficient content delivery, mobility, and multihoming, location independent name prefixes are hard to aggregate. This poses a serious scaling issue on the efficiency of looking up content names in a huge Forwarding Information Base (FIB) by longest prefix matching, which requires seeking the longest matching prefix through all candidate prefix lengths. We propose a new scheme for efficiently looking up non-aggregatable name prefixes in a large FIB. The proposed scheme is based on the observation that the bottleneck of FIB lookup is the random accesses to the high-latency off-chip DRAM for prefix seeking and this can be reduced by exploiting the information on the longest matching prefix length in the previous hop. Our evaluation results show that the proposed scheme significantly improves FIB lookup latency with a reasonable traffic parameters observed in today's Internet.

Recently, there has been a surge of interest in Artificial Intelligence (AI) and its applications have been considered in various fields. Mobile networks are becoming an indispensable part of our society, and are considered as one of the promising applications of AI. In the Beyond 5G/6G era, AI will continue to penetrate networks and AI will become an integral part of mobile networks. This paper provides an overview of the collaborations between networks and AI from two categories, “AI for Network” and “Network for AI,” and predicts mobile networks in the B5G/6G era. It is expected that the future mobile network will be an integrated infrastructure, which will not only be a mere application of AI, but also provide as the process infrastructure for AI applications. This integration requires a driving application, and the network operation is one of the leading candidates. Furthermore, the paper describes the latest research and standardization trends in the autonomous networks, which aims to fully automate network operation, as a future network operation concept with AI, and discusses research issues in the future mobile networks.

Information-Centric Networking (ICN) can offer rich functionalities to the network, e.g, in-network caching, and name-based forwarding. Incremental deployment of ICN is a key challenge that enable smooth migration from current IP network to ICN. We can say that Network Function Virtualization (NFV) must be one of the key technologies to achieve this deployment because of its flexibility to support new network functions. However, when we consider the ICN deployment with NFV, there exist two performance issues, processing delay of name-based forwarding and computational overhead of virtual machine. In this paper we proposed a NFV infrastructure-assisted ICN packet forwarding by integrating the name look-up to the Open vSwitch. The contributions are twofold: 1) First, we provide the novel name look-up scheme that can forward ICN packets without costly longest prefix match searching. 2) Second, we design the ICN packet forwarding scheme that integrates the partial name look-up into the virtualization infrastructure to mitigate computation overhead.

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.

Content-centric networking (CCN) is an emerging networking architecture that is being actively investigated in both the research and industrial communities. In the latest version of CCN, a large number of interests have to be issued when large content is retrieved. Since CCN routers have to search several tables for each incoming interest, this could cause a serious problem of router workload. In order to solve this problem, this paper introduces a novel strategy of “grouping” multiple interests with common information and “packing” them to a special interest called the list interest. Our list interest is designed to co-operate with the manifest of CCN as its dual. This paper demonstrates that by skipping and terminating several search steps using the common information in the list interest, the router can search its tables for the list interest-based request with dramatically smaller complexity than the case of the standard interest-based request. Furthermore, we also consider the deployment of list interests and design a novel TCP-like congestion control method for list interests to employ them just like standard interests.

A global content delivery plays an important role in the current Internet. Information-Centric Networking (ICN) is a future internet architecture which attempts to redesign the Internet with a focus on the content delivery. However, it has the potential performance degradation in the global content delivery. In this paper, we propose an ICN performance enhancing proxy (ICN-PEP) to mitigate this performance degradation. The key idea is to prefetch Data packets and to serve them to the consumer with the shorter round trip time. By utilizing ICN features, it can be developed as an offline and state-less proxy which has an advantage of scalability. We evaluate the performance of ICN-PEP in both simulation and experiment on global testbed and show that ICN-PEP improves the performance of global content delivery.

In forthcoming sensor networks, a multitude of sensor nodes deployed over a large geographical area for monitoring traffic, climate, etc. are expected to become an inevitable infrastructure. Clustering algorithms play an important role in aggregating a large volume of data that are produced continuously by the huge number of sensor nodes. In such networks, equal-sized multi-hop clusters which include an equal number of nodes are useful for efficiency and resiliency. In addition, scalability is important in such large-scale networks. In this paper, we mathematically design a decentralized equal-sized clustering algorithm using a partial differential equation based on the Fourier transform technique, and then design its protocol by discretizing the equation. We evaluated through simulations the equality of cluster sizes and the resiliency against packet loss and node failure in two-dimensional perturbed grid topologies.

In the 5G era, centralized mobility management raises the issue of traffic concentration on the mobility anchor. Distributed mobility management is expected to be a solution for this issue, as it moves mobility anchor functions to multiple edge routers. However, it incurs path stretch and redundant traffic on the backhaul links. Although these issues were not considered important in the 3G/4G era, they are expected to be a serious problem in the 5G era. In this paper, we design a routing-based mobility management mechanism to address the above problems. The mechanism integrates distributed routing with Bloom Filters and an anchor-less scheme where edge routers work as mobility anchors. Simulations show that the proposed mechanism achieves a good balance between redundant traffic on the backhaul links and routing overhead.