Broadband fixed wireless access (BFWA) systems with multi-hop mesh topologies have attracted considerable attention as a promising technology for next generation, high quality, high capacity, and high density access infrastructures. The primary advantages of mesh network topologies are an improvement of capacity by means of traffic engineering throughout the networks. This paper discusses an adaptive traffic load balancing method that maximizes the capacity for the mesh BFWA networks. Taking into account the variation of network conditions such as traffic demand distributions and qualities of wireless links, the adaptive traffic load balancing method attempts to equalize the utilization of capacity for each wireless link. To avoid deteriorating the performance of TCP communications, the proposed method implements flow-based traffic load balancing. Performance of the proposed adaptive traffic load balancing method is demonstrated and validated using the experimental mesh network environments with wired networks with up to sixteen nodes that emulates the variation of the wireless link capacity.

Active network monitoring based on Boolean network tomography is a promising technique to localize link failures instantly in transport networks. However, the required set of monitoring trails must be recomputed after each link failure has occurred to handle succeeding link failures. Existing heuristic methods cannot compute the required monitoring trails in a sufficiently short time when multiple-link failures must be localized in the whole of large-scale managed networks. This paper proposes an approach for computing the required monitoring trails within an allowable expected period specified beforehand. A random walk-based analysis estimates the number of monitoring trails to be computed in the proposed approach. The estimated number of monitoring trails are computed by a lightweight method that only guarantees partial localization within restricted areas. The lightweight method is repeatedly executed until a successful set of monitoring trails achieving unambiguous localization in the entire managed networks can be obtained. This paper demonstrates that the proposed approach can compute a small number of monitoring trails for localizing all independent dual-link failures in managed networks made up of thousands of links within a given expected short period.

A 64-bit architecture for an embedded processor targeted for next-generation digital consumer products has been developed. It has dual-mode instruction sets and is optimized for high multimedia performance, provided by SIMD/floating-point vector instructions in 32-bit length ISA, and small code size, provided by a conventional 16-bit length ISA. Large register files, (6464b and 6432b), a split-branch mechanism, and virtual cache are also adopted in the architecture. A 714MIPS/9.6 GOPS/400 MHz processor core with the 64-bit architecture and a system LSI containing the core are developed using 0.15-µm technology. The LSI includes a 3.2 GB/sec high-bandwidth on-chip bus, a high-speed DRAM interface, a SRAM/Flash/ROM/Multiplexed-bus interface, and a 66 MHz PCI interface that provide the performance required for next-generation multimedia applications.

Application-aware Traffic Engineering (TE) plays a crucial role in ensuring quality of services (QoS) for recently emerging applications such as AR, VR, cloud gaming, and connected vehicles. While a deterministic application-aware TE is required for these mission-critical applications, a negotiation procedure between applications and network operators needs to undergo major simplification to fulfill the scalability of the application based on emerging microservices and container-based architecture. In this paper, we propose a NetworkAPI framework which allows an application to indicate a desired TE behavior inside IP packets by leveraging Segment Routing over IPv6 (SRv6). In the NetworkAPI framework, the TE behavior provided by the network operator is expressed as an SRv6 Segment Identifier (SID) in the form of a 128-bit IPv6 address. Because the IPv6 address of an SRv6 SID is distributed using IP anycast, the application can utilize the unchanged SRv6 SID regardless of the application's location, as if the application controls an API on the transport network. We implement a prototype of the NetworkAPI framework on a Linux kernel. On the prototype implementation, a basic packet forwarding performance is evaluated to demonstrate the feasibility of our framework.

Broadband fixed wireless access (BFWA) systems with multi-hop mesh topologies have attracted considerable attention as a promising technology for next generation, high quality, high capacity, and high density access infrastructures. The primary advantages of mesh network topologies are an improvement of availability in connectivity between pairs of nodes by means of diversity routes. This paper discusses wireless node architecture that enables the integrated control of route diversity and traffic engineering together with the control of wireless links whose quality and performance could be affected by radio propagation conditions. Taking into account the functional requirements for multi-hop mesh BFWA networks, such as adaptive link configuration with multiple channels, distributed network management, and traffic engineering in mesh networks, the entity called network control unit (NCU) is designed and developed on a common UNIX based server computer. Implemented functions and their performance are demonstrated using the experimental environments with wired networks.

Peer-to-peer overlay networks can easily achieve a large-scale content sharing system on the Internet. Although unstructured peer-to-peer networks are suitable for finding entire partial-match content, flooding-based search is an inefficient way to obtain target content. When the shared content is semantically specified by a great number of attributes, it is difficult to derive the semantic similarity of peers beforehand. This means that content search methods relying on interest-based locality are more advantageous than those based on the semantic similarity of peers. Existing search methods that exploit interest-based locality organize multiple peer groups, in each of which peers with common interests are densely connected using short-cut links. However, content searches among multiple peer groups are still inefficient when the number of incident links at each peer is limited due to the capacity of the peer. This paper proposes a novel content search method that exploits interest-based locality. The proposed method can organize an efficient peer-to-peer network similar to the semantic small-world random graph, which can be organized by the existing methods based on the semantic similarity of peers. In the proposed method, topology transformation based on local link replacement maintains the numbers of incident links at all the peers. Simulation results confirm that the proposed method can achieve a significantly higher ratio of obtainable partial-match content than existing methods that organize peer groups.

Since traffic in IP access networks is less aggregated than in backbone networks, its variance could be significant and its distribution may be long-tailed rather than Gaussian in nature. Such characteristics make it difficult to forecast traffic volume in IP access networks for appropriate capacity planning. This paper proposes a traffic forecasting method that includes a function to control residual error distribution in IP access networks. The objective of the proposed method is to grasp the statistical characteristics of peak traffic variations, while conventional methods focus on average rather than peak values. In the proposed method, a neural network model is built recursively while weighting residual errors around the peaks. This enables network operators to control the trade-off between underestimation and overestimation errors according to their planning policy. Evaluation with a total of 136 daily traffic volume data sequences measured in actual IP access networks demonstrates the performance of the proposed method.