論文

RHiNET-3/SW is the third-generation switch used in the RHiNET-3 system. It provides both low-latency processing and flexible connection due to its use of a credit-based flow-control mechanism, topology-free routing, and deadlock-free routing. The aggregate throughput of RHiNET-3/SW is 80 Gbps, and the latency is 140 ns. RHiNET-3/SW also provides a hop-by-hop retransmission mechanism. Simulation demonstrated that the effective throughput at a node in a 64-node torus RHiNET-3 system is equivalent to the effective throughput of a 64-bit 33-MHz PCI bus and that the performance of RHiNET-3/SW almost equals or exceeds the best performance of RHiNET-2/SW, the second-generation switch. Although credit-based flow control requires 26% more gates than rate-based flow control to manage the virtual channels (VCs), it requires less VC memory than rate-based flow control. Moreover, its use in a network system reduces latency and increases the maximum throughput compared to rate-based flow control.

© 2016 IEEE. Smart Grids and Home Energy Management System (HEMS) have been propagated by energy liberalization, and there is a demand for services, which are based on analysis of energy consumption data. For instance, a recommendation on effective utilization of home appliances in order to reduce power consumption. However, it is computationally expensive to analyze data in order to provide an energy-saving handbook, which recommends low-carbon life and is written in a natural language. This kind of service is called recommendation service. Existing automated recommendation services are constrained by the range of data usage, especially when using local information, such as status of surroundings, weather, residents' behavior, etc. The proposed method of automated generation of recommendation considers this background knowledge and information by using clustering methods. The result of a questionnaire which compared a handmade recommendation with the proposed fully-automated recommendation showed that 80% of the residents selected the automated recommendation because of its appropriateness.

This study is focused on hardware-based anonymization of location data for addressing privacy concerns while maintaining data utility in applications such as traffic-congestion prediction. The anonymization process involves approximating user location data to map intersections, identifying trajectories, and applying k-anonymization. However, the processing time in software implementation should be minimized. For real-time services, the process must be completed within 30 s to 1 min, which corresponds to the information update interval. Service requirements cannot be met when the volume of data and the scale of maps increase. To address this issue, we implemented a hardware accelerator on an field programmable gate array to perform the process with the aim of reducing the processing time. As a result, the maximum throughput of the proposed mechanism was approximately 150,000 data/s, which surpasses the target value of 130,000 data/s. The data retention rate, which represents information loss, was approximately 90% for the commonly used range of 10≤ k≤ 20. The difference in the data retention rate compared with the software implementation was approximately 1%. These results confirmed the effectiveness of the anonymization results obtained using the proposed mechanism.

Object detection and tracking technology are essential in many ways with the increasing demand for remote video conferencing and video surveillance. This paper focuses on a method that combines an object detection method based on a CNN (Convolutional Neural Network) with a motion-vector-based object tracking method in specified frames instead of the whole frame stream. Although this method can improve the throughput with a small memory requirement, it requires 3D image filters to reduce the noise in each motion vector. The immense computing power needed for 3D image filters prevents this method from being popularly used. To address this problem, we propose to implement the technique on an FPGA and offload the filters and CNN engine on the FPGA hardwired logic. We implemented slide window-based image filters on a Zynq Ultrascale+ FPGA board and achieved 23.42 times performance improvement for the median filter and 55.46 times for the average filter, respectively. Considering the resource usage, it appeared that we could implement these 3D image filters design with YOLO on the target FPGA.

Anomaly detection is one of the key applications of data utilization in smart factories, particularly in monitoring factory facilities. Early detection and resolution of anomalies, such as system failures, can lead to cost reduction and quality stabilization. One of the targets of abnormality detection applications in the industry section is a refrigerator unit used in food processing factories and warehouses. Anomalies in the early stages in refrigerator units appear in the operating sounds, which can enable their detection. In this study, we propose a method for detecting abnormal sound, extracting abnormal frequency components, and identifying the direction of the abnormal sound source. To identify the direction of the anomalous sound source, multi-channel sound recorded by a microphone array is used. To the best of our knowledge, no method has yet been proposed for anomaly sound detection using multi-channel acoustic data. In the proposed method, anomaly scores calculated in each channel of the microphone array are aggregated to determine whether the entire data is anomalous or not. Anomalous sounds were extracted from the anomaly data using a deep generative model. The extracted anomalous sounds were used to localize the sound source and the direction of the anomalous source was identified. The proposed method improved the precision of anomaly sound detection while maintaining the recall rate of a conservative comparison method. Using the proposed method, anomalous sounds were extracted from the anomaly data, and their arrival directions were identified.

Decentralized control is a promising method with many advantages while an effective design method for it is desired. Design in conventional methods is complicated because the correspondence between a system role and its controllers is unclear. To solve this problem, we have proposed the idea of "functionality" for a bilateral control system. The idea is to divide the system role into minimum components. The design method based on this idea is clear since controllers correspond to respective functions. Furthermore, the design method is simple since each function is a minimum component. This study expands the idea of the functionality to design of decentralized control systems. Subsystems are constructed based on functions. Functions for normal operation and for exception handling are treated in a unified manner. The system can automatically sustain important functions by a priority order of functions. This method realizes simple and explicit controller design for a decentralized control system with exception handling. Simulation and experimental results show the flexibility, fault tolerance and expandability of the decentralized system.

Haptic sense is indispensable for skillful operation in a telerobotic system. Bilateral control attracts considerable interest because it transfers the haptic sense to a remote place. Although it is simply composed of two manipulators, its design is complicated. This study proposes an idea that provides a new framework on design of a bilateral control system. The idea is to design the bilateral control system based on a "function", a minimum component of a system role. It enables simple and explicit design for various tasks. The features of the proposed method provide a way to design an adjustable system. Experimental results show the validity of the proposed method.

A high-speed physical-layer architecture for Ethernet is described that supports 100-Gb/s throughput and 40-km transmission, making it well suited for next-generation metro-area and intrabuilding networks. Its links comprise 12 × 10-Gb/s synchronized parallel optical lanes. Ethernet data frames are transmitted by coarse wavelength division multiplexing link and bundled optical fibers. Ten of the lanes convey 640-bit data synchronously (64 bits × 10 lanes). One conveys forward error correction code ((132 b, 140 b) Hamming code), providing highly reliable (BER < 10-12) data transmission, and the other conveys parity data, enabling fault-lane recovery. A newly developed 64B/66B code-sequence-based deskewing mechanism is used that provides low-latency compensation for the lane-to-lane skew, which is less than 88 ns. Testing of this physical-layer architecture in a field programmable gate array circuit demonstrated that it can provide 100-Gb/s data communication with a 590 k gate circuit, which is small enough for implementation in a single LSI circuit. Copyright © 2006 The Institute of Electronics, Information and Communication Engineers.

Smart meters for measuring electricity usage are expected in electricity usage management. Although the relevant power supplier stores the measured data, the data are worth sharing among power suppliers because the entire data of a city will be required to control the regional grid stability or demand–supply balance. Even though many techniques and methods of privacy-preserving data mining have been studied to share data while preserving data privacy, a study on sharing electricity usage data is still lacking. In this paper, we propose a sharing method of electricity usage while preserving data privacy using a self-organizing map.

An ultra high-speed Ethernet subsystem, which realizes 100-Gb/s throughput and transmission up to 40 km, is examined for next-generation metro-area networks. A parallel link of 12 10-Gb/s synchronized parallel optical lanes is proposed. The 10 optical lanes are used to transmit 10-bit parallel data. The one of redundant lanes transmits a forward error correction code ((132b, 140b) Hamming code) to achieve highly-reliable (BER < 10-12) data transmission, and the other lane transmits a parity data used for the fault-lane recovery. Here, a 64B/66B code-sequence-based de-skewing mechanism is proposed, and its effectiveness to realize low-latency compensation of the inter-lane skew (< 80 ns) is shown. We have implemented the 100-Gb-Ethernet interface architectures into FPGA circuits, and confirmed the performance of 100 Gb/s data communication with compact 385-kgates circuit size, which is practically small for implementation in a single LSI circuit. © 2005 IEEE.

The authors have developed a communications architecture called RHiNET that is capable of high-performance parallel processing by interconnecting PCs and WSs. RHiNET uses not only computers concentrated in one place but also computers used for daily business within buildings and within floors for parallel processing. Networks used by RHiNET should have high effective bandwidths and small latencies for high-efficiency computing, as well as link lengths for connecting the computers within buildings and floors and a free topology. The former requirements are not satisfied sufficiently by the conventional LANs, while the latter is not satisfied by SANs which are used in cluster systems. RHiNET satisfies both conditions by using a switch having a large memory capacity. In this paper, the architecture and implementation of the RHiNET/SW1 switch used by RHiNET networks are discussed. A scheme called virtual cache is used in RHiNET/SW1 such that a large-capacity packet buffer is installed by SRAM outside the switch ASIC. In addition, the performance of the switch is evaluated by a simulator. © 2001 Scripta Technica, Syst. Comp. Jpn.

DIMMnet-1 is a high-performance network interface for a PC cluster system. It uses memory bus for IO bus to relax a bottleneck of networks. Moreover, a PC memory bus is spread bandwidth earliest in a PC, the DIMMnet-1 can reorganize a NIC according to spreading bandwidth of a communication link. However, the NIC that use a parallel transmission lacks a scalability of a bandwidth of a communication link. To resolve this problem, we developed new NICs : DIMMnet-1/bDais and DIMMnet-2. We employ a high-speed serial transmission on these NICs. Therefore we have to expand the DIMMnet network protocol. Now we have been developing new DIMMnet network protocol by two parts. The One is the CoreLogic which includes communication primitives. In this paper, we describe the rest of that which is the InfiniSWIF that includes functions of packet forwarding. And we propose the Concurrent Datagram communication service which is implemented in the InfiniSWIF and gives reliability and scalability for the DIMMnet network protocol.

As a peak-cut or peak leveling control, heating, ventilation, and air conditioning (HVAC) are essential method for controlling the demand of electric power consumption. However, it is important to consider environmental amenity when designing control systems because the control may cause the deterioration of the amenity. In existing methods, metabolic equivalent (MET) values are not considered. Measurement and processing of MET values can be costly, requiring special infrastructure to both measure the values and communicate these values with a home energy management system (HEMS) or building energy management system (BEMS). This paper proposes a HVAC control method that considers the tradeoff between environmental amenity and energy conservation using the Keio University network oriented intelligent and versatile energy management system (KNIVES). The proposed method uses an iPod touch or iPhone application to obtain accurate measurements of both the MET value and the predicted mean vote (PMV). The accuracy of the PMV values after incorporation of MET estimates was confirmed experimentally. A HEMS experiment was conducted and a reduction in energy consumption was observed, demonstrating the usefulness of both the application and the proposed HVAC control method. © 2013 IEEE.

Industrialized insect-based bioconversion is a technologically promising and economical viable approach for solving global crisis of food security and waste management. The successful implementation of such a multi-disciplinary system requires comprehensive expertise and skills from biotechnology, automation, information, and circular economy domains. This is rather difficult for existing practitioners. To simplify their jobs, by leveraging recent advances in industrial informatics, this work proposed and developed a low-code development platform for engineering the automation logic of industrial insect rearing and processing. For feasibility demonstration, a pilot facility has been designed, deployed, and benchmarked in this work. When compared with the conventional pro-code practice, the proposed low-code approach can significantly reduce development costs, shorten delivery times, and improve communication efficiency.

Simulating differential equations on classical computers becomes an intractable problem if the grid size is extremely large. Quantum computers are believed to achieve a possibly exponential speedup in the matrix operation. In this paper, we propose a quantum algorithm for solving the advection-diffusion-reaction equation by employing a novel approximate probabilistic imaginary-time evolution (PITE) operator. First, the effectiveness of the proposed approximate PITE operator is justified by the theoretical evaluation of the error. Next, we construct the explicit quantum circuit to realize the imaginary-time evolution of the Hamiltonian coming from the advection-diffusion equation, whose gate complexity is logarithmic regarding the size of the discretized Hamiltonian matrix. Compared to the existing algorithms for the quantum linear system problem, our algorithm achieves an exponential speedup regarding the matrix size at the cost of a worse dependence on the error bound. Moreover, numerical simulations using gate-based quantum emulator for 1D/2D examples are also provided to verify our algorithm. Finally, we extend our algorithm to the coupled system of advection-diffusion equations to show the prospects for practical applications.

Copyright © 2016 The Institute of Electronics, Information and Communication Engineers. Changing attitudes toward energy security and energy conservation have led to the introduction of distributed power systems such as photovoltaic, gas-cogeneration, biomass, water, and wind power generators. The mass installation of distributed energy generators often causes instability in the voltage and frequency of the power grid. Moreover, the power quality of distributed power grids can become degraded when system faults or the activation of highly loaded machines cause rapid changes in power load. To avoid such problems and maintain an acceptable power quality, it is important to detect the source of these rapid changes. To address these issues, next-generation power grids that can detect the fault location have been proposed. Fault location demands accurate time synchronization. Conventional techniques use the Global Positioning System (GPS) and/or IEEE 1588v2 for time synchronization. However, both methods have drawbacks-GPS cannot be used in indoor situations, and the installation cost of IEEE 1588v2 devices is high. In this paper, a time synchronization technique using the broadcast function of an Ethernet Passive Optical Network (EPON) system is proposed. Experiments show that the proposed technique is low-cost and useful for smart grid applications that use time synchronization in EPON-based next-generation power grids.

In recent years, the volume of captured location-based movement data has drastically increased with the prevalence of smartphones. Mobility data are commonly used for smart assistant and personalized advertising applications. However, such data contain considerable sensitive information; thus, they must be anonymized before they can be published or analyzed. In this study, we investigate the problem of anonymization for trajectory publication. Anonymizing trajectories is challenging because they have high dimensionality in both the spatial and temporal domains. Traditional anonymization methods cannot handle high dimensionality without significantly sacrificing data utility. The proposed method addresses this limitation by training a Seq2Seq autoencoder model to reconstruct trajectories from the spatiotemporal input, followed by distributing the Laplace noise to the principal components of the Seq2Seq encoder's hidden-layer output under differential privacy. By distributing the privacy budget in the latent space, the proposed method can output trajectories that satisfy differential privacy while maintaining embedded information. Experimental results from the application of the proposed method to real-life movement trajectory data from Saitama, Japan, demonstrate a reduction in data loss by up to 75.7 % while maintaining significant data utility.

© 2017 IEEE. The spread of smart meters means that a large amount of power demand information from private houses is being collected around the world. Owing to the development of smart city infrastructure, the use of standardized frameworks for extracting features from power demand information has become vital. In this paper, we propose a novel decomposition approach useful for extracting feature values from power demand information from a house. Energy consumption was monitored for multiple houses for one month in Japan with a sampling duration of 30 minutes, which is a standard sampling time of smart meters in Japan. First, periodic characteristics were detected for 24 hours based on autocorrelation analysis. Then, the monitored information was decomposed into four components: standby power, trends, and periodic and residual parts. The distribution of the residual part is similar to a Gaussian distribution, so the behavior of the residual part was parameterized using variance and average. Trend, periodic, and residual components were clustered by means of k-means clustering in order to aggregate the difference in behaviors. There was no periodic component in the residual part according to auto-correlation analysis. Nevertheless, some clusters had a relatively large variance, which means that abnormal power demand occurred frequently in datasets. The amount of variance and climate correlation was analyzed, and the fact detected that large scale events disturb usual daily life-styles, from the viewpoint of energy usage. Last, these features were compared with actual customer information. In the evaluation, family structure and floor space were utilized to prove the effectiveness of the proposed decomposition approach. The evaluation proved that this decomposition method could extract uncertainty features from power demand information.

様々なインフラに情報通信技術を投入しつつ融合させたスマートコミュニティにおいては,スマートメータによる電力利用情報や,家庭向けエネルギー管理システムによる環境,生活情報,利用者の行動情報,気象情報,医療情報など,様々な情報が取得,活用される.これらを横断的に解析して新しい知見を入手,提供することや,本来の目的とは異なる目的で利用するなど,新しいサービスの展開が期待されている.本稿では,スマートコミュニティ向けサービスを構築する上で必要となる,プライバシー問題の解決といった情報の扱い方,必要となるインフラ,具体的なサービス事例について解説する.