arXiv subjects

Yoji Yamato

Publications and source records attributed to Yoji Yamato.

At least 19 recordsLinked to original sources

arXiv2024

Security Camera Movie and ERP Data Matching System to Prevent Theft

"(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." In this paper, we propose a SaaS service which prevents shoplifting using image analysis and ERP. In Japan, total damage of shoplifting reaches 450 billion yen. Based on cloud and data analysis technology, we propose a shoplifting prevention service with image analysis of security camera and ERP data check for small shops. We evaluated movie analysis. Y. Yamato, Y. Fukumoto and H. Kumazaki, "Security Camera Movie and ERP Data Matching System to Prevent Theft," IEEE Consumer Communications and Networking Conference (CCNC 2017), pp.1021-1022, DOI: 10.1109/CCNC.2017.7983275, Jan. 2017.

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arXiv2024

Experiments of posture estimation on vehicles using wearable acceleration sensors

In this paper, we study methods to estimate drivers' posture in vehicles using acceleration data of wearable sensor and conduct a field test. Recently, sensor technologies have been progressed. Solutions of safety management to analyze vital data acquired from wearable sensor and judge work status are proposed. To prevent huge accidents, demands for safety management of bus and taxi are high. However, acceleration of vehicles is added to wearable sensor in vehicles, and there is no guarantee to estimate drivers' posture accurately. Therefore, in this paper, we study methods to estimate driving posture using acceleration data acquired from T-shirt type wearable sensor hitoe, conduct field tests and implement a sample application. Y. Yamato, "Experiments of Posture Estimation on Vehicles Using Wearable Acceleration Sensors," The 3rd IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2017), pp.14-17, DOI: 10.1109/BigDataSecurity.2017.8, May 2017. "(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."

cs.HC↗

arXiv2024

A Study to Optimize Heterogeneous Resources for Open IoT

Recently, IoT technologies have been progressed, and many sensors and actuators are connected to networks. Previously, IoT services were developed by vertical integration style. But now Open IoT concept has attracted attentions which achieves various IoT services by integrating horizontal separated devices and services. For Open IoT era, we have proposed the Tacit Computing technology to discover the devices with necessary data for users on demand and use them dynamically. We also implemented elemental technologies of Tacit Computing. In this paper, we propose three layers optimizations to reduce operation cost and improve performance of Tacit computing service, in order to make as a continuous service of discovered devices by Tacit Computing. In optimization process, appropriate function allocation or offloading specific functions are calculated on device, network and cloud layer before full-scale operation. Y. Yamato, N. Hoshikawa, H. Noguchi, T. Demizu and M. Kataoka, "A Study to Optimize Heterogeneous Resources for Open IoT," The Fifth International Symposium on Computing and Networking (CANDAR 2017), pp.609-611, DOI: 10.1109/CANDAR.2017.16, Nov. 2017. "(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."

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arXiv2024

Proposal of Automatic Offloading Method in Mixed Offloading Destination Environment

When using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration. However, including existing technologies, there has been no research to properly and automatically offload the mixed offloading destination environment such as GPU, FPGA and many core CPU. In this paper, as a new element of environment-adaptive software, I study a method for offloading applications properly and automatically in the environment where the offloading destination is mixed with GPU, FPGA and many core CPU. Y. Yamato, "Proposal of Automatic Offloading Method in Mixed Offloading Destination Environment," 2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW 2020), pp.460-464, DOI: 10.1109/CANDARW51189.2020.00094, Nov. 2020. "(c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."

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arXiv2023

Proposal of appropriate location calculations for environment adaptation

To use heterogeneous hardware, programmers must have sufficient technical skills to utilize OpenMP, CUDA, and OpenCL. On the basis of this, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, in accordance with the hardware. However, although it has been considered to convert the code according to the offload devices, there has been no study where to place the offloaded applications to satisfy users' requirements of price and response time. In this paper, as a new element of environment-adapted software, I examine a method to calculate appropriate locations using linear programming method. I confirm that applications can be arranged appropriately through simulation experiments when some conditions such as application type and users' requirements are changed.

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arXiv2023

Proposal of Real Time Predictive Maintenance Platform with 3D Printer for Business Vehicles

This paper proposes a maintenance platform for business vehicles which detects failure sign using IoT data on the move, orders to create repair parts by 3D printers and to deliver them to the destination. Recently, IoT and 3D printer technologies have been progressed and application cases to manufacturing and maintenance have been increased. Especially in air flight industry, various sensing data are collected during flight by IoT technologies and parts are created by 3D printers. And IoT platforms which improve development/operation of IoT applications also have been appeared. However, existing IoT platforms mainly targets to visualize "things" statuses by batch processing of collected sensing data, and 3 factors of real-time, automatic orders of repair parts and parts stock cost are insufficient to accelerate businesses. This paper targets maintenance of business vehicles such as airplane or high-speed bus. We propose a maintenance platform with real-time analysis, automatic orders of repair parts and minimum stock cost of parts. The proposed platform collects data via closed VPN, analyzes stream data and predicts failures in real-time by online machine learning framework Jubatus, coordinates ERP or SCM via in memory DB to order repair parts and also distributes repair parts data to 3D printers to create repair parts near the destination.

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arXiv2022

Server Structure Proposal and Automatic Verification Technology on IaaS Cloud of Plural Type Servers

In this paper, we propose a server structure proposal and automatic performance verification technology which proposes and verifies an appropriate server structure on Infrastructure as a Service (IaaS) cloud with baremetal servers, container based virtual servers and virtual machines. Recently, cloud services have been progressed and providers provide not only virtual machines but also baremetal servers and container based virtual servers. However, users need to design an appropriate server structure for their requirements based on 3 types quantitative performances and users need much technical knowledge to optimize their system performances. Therefore, we study a technology which satisfies users' performance requirements on these 3 types IaaS cloud. Firstly, we measure performances of a baremetal server, Docker containers, KVM (Kernel based Virtual Machine) virtual machines on OpenStack with virtual server number changing. Secondly, we propose a server structure proposal technology based on the measured quantitative data. A server structure proposal technology receives an abstract template of OpenStack Heat and function/performance requirements and then creates a concrete template with server specification information. Thirdly, we propose an automatic performance verification technology which executes necessary performance tests automatically on provisioned user environments according to the template.

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arXiv2022

Proposal of FPGA logic change after service launch for environment adaptation

In order to make full use of heterogeneous hardware, it is necessary to have a technical skill of hardware such as OpenCL, and the current situation is that the barrier is high. Based on this background, I have proposed environment-adaptive software that enables high-performance operation by automatically converting application code written for normal CPUs by engineers according to the deployed environment and setting appropriate amount of resources. Until now, I only considered conversions and settings before the start of operation. In this paper, I verify that the logic is reconfigured according to the usage characteristics during operation. I confirm that the application running on the FPGA is reconfigured into another application according to the usage characteristics.

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arXiv2022

Proposal of deployment reconfiguration for environment adaptation

To use heterogeneous hardware, programmers needed sufficient technical skills such as OpenMP, CUDA, and OpenCL. Therefore, I have proposed environment-adaptive software that enables high-performance operation by automatically converting and configuring the code once written, and have been working on automatic conversion and proper placement. However, until now, where to initially place the converted application has been considered, but the overall optimal placement has not been considered in consideration of the placement status of other users. In this paper, as a new element of environment-adaptive software, I study the relocation during operation, which improves the overall user satisfaction by considering the placement of other users, using a linear programming method. It was confirmed that it can be properly rearranged through simulation experiments.

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arXiv2022

Application placement study of environment adaptive software

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arXiv2021

Power Saving Evaluation with Automatic Offloading

Heterogeneous hardware other than small-core CPU such as GPU, FPGA, or many-core CPU is increasingly being used. However, heterogeneous hardware usage presents high technical skill barriers such as familiarity with CUDA. To overcome this challenge, I previously proposed environment-adaptive software that enables automatic conversion, automatic configuration, and high-performance and low-power operation of once-written code, in accordance with the hardware to be placed. I also previously verified performance improvement of automatic GPU and FPGA offloading. In this paper, I verify low-power operation with environment adaptation by evaluating power utilization after automatic offloading. I compare Watt*seconds of existing applications after automatic offloading with the case of CPU-only processing.

cs.AR↗

arXiv2021

Power Reduction of Automatic Heterogeneous Device Offloading

In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as CUDA are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance and low power operation of once written code, according to the hardware to be placed. I also have verified performance improvement of automatic GPU and FPGA offloading so far. In this paper, I verify low power operation with environment adaptation by confirming power utilization after automatic offloading. I compare Watt*seconds of existing applications after automatic offloading with the case of CPU only processing.

cs.DC↗

arXiv2021

Study of Automatic Offloading Method in Mixed Offloading Destination Environment

In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, according to the hardware to be placed. However, including existing technologies, there has been no research to properly and automatically offload the mixed offloading destination environment such as GPU, FPGA and many core CPU. In this paper, as a new element of environment-adaptive software, I study a method for offloading applications properly and automatically in the environment where the offloading destination is mixed with GPU, FPGA and many core CPU. I evaluate the effectiveness of the proposed method in multiple applications.

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arXiv2020

Study of Resource Amount Configuration for Automatic Application Offloading

In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, according to the hardware to be placed. However, although the conversion of the code according to the migration destination environment has been studied so far, there has been no research to properly set the resource amount. In this paper, as a new element of environment adaptive software, in order to operate the application with high cost performance, I study a method to optimize the resource amount of CPUs and offload devices.

cs.DC↗

arXiv2020

Study of Automatic GPU Offloading Method from Various Language Applications

In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as CUDA are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, according to the hardware to be placed. However, the source language for offloading was mainly C/C++ language applications currently, and there was no research for common offloading for various language applications. In this paper, I study a common method for automatically offloading for various language applications not only in C language but also in Python and Java.

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arXiv2020

Proposal of Automatic Offloading for Function Blocks of Applications

When using heterogeneous hardware other than CPUs, barriers of technical skills such as OpenCL are high. Based on that, I have proposed environment adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code, according to the hardware to be placed. Partly of the offloading to the GPU was automated previously. In this paper, I propose and evaluate an automatic extraction method of appropriate offload target loop statements of source code as the first step of offloading to FPGA. I evaluate the effectiveness of the proposed method in multiple applications.

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arXiv2020

Proposal of Automatic FPGA Offloading for Applications Loop Statements

In recent years, with the prediction of Moore's law slowing down, utilization of hardware other than CPU such as FPGA which is energy effective is increasing. However, when using heterogeneous hardware other than CPUs, barriers of technical skills such as OpenCL are high. Based on that, I have proposed environment adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code, according to the hardware to be placed. Partly of the offloading to the GPU was automated previously. In this paper, I propose and evaluate an automatic extraction method of appropriate offload target loop statements of source code as the first step of offloading to FPGA. I evaluate the effectiveness of the proposed method using existing applications.

cs.DC↗

arXiv2020

Evaluation of Automatic GPU and FPGA Offloading for Function Blocks of Applications

In the recent years, systems using FPGAs, GPUs have increased due to their advantages such as power efficiency compared to CPUs. However, use in systems such as FPGAs and GPUs requires understanding hardware-specific technical specifications such as HDL and CUDA, which is a high hurdle. Based on this background, I previously proposed environment adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code according to the hardware to be placed. As an element of the concept, I proposed a method to automatically offload loop statements of application source code for CPU to FPGA and GPU. In this paper, I propose and evaluate a method for offloading a function block, which is a larger unit, instead of individual loop statements in an application, to achieve higher speed by automatic offloading to GPU and FPGA. I implement the proposed method and evaluate with existing applications offloading to GPU.

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