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A study in resource federation for e-Science
https://ir.soken.ac.jp/records/3580
https://ir.soken.ac.jp/records/358099859aa0-f496-4c39-85fd-9c3741054494
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要旨・審査要旨 (278.8 kB)
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本文 (3.8 MB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||||
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| 公開日 | 2013-06-10 | |||||||
| タイトル | ||||||||
| タイトル | A study in resource federation for e-Science | |||||||
| タイトル | ||||||||
| タイトル | A study in resource federation for e-Science | |||||||
| 言語 | en | |||||||
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| 言語 | eng | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_46ec | |||||||
| 資源タイプ | thesis | |||||||
| 著者名 |
河井, 裕
× 河井, 裕
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| フリガナ |
カワイ, ユタカ
× カワイ, ユタカ
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| 著者 |
KAWAI, Yutaka
× KAWAI, Yutaka
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| 学位授与機関 | ||||||||
| 学位授与機関名 | 総合研究大学院大学 | |||||||
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| 学位名 | 博士（工学） | |||||||
| 学位記番号 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 総研大甲第1548号 | |||||||
| 研究科 | ||||||||
| 値 | 高エネルギー加速器科学研究科 | |||||||
| 専攻 | ||||||||
| 値 | 12 加速器科学専攻 | |||||||
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| 学位授与年月日 | 2012-09-28 | |||||||
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| 値 | 2012 | |||||||
| 要旨 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | This research seeks to seamlessly support the infrastructure of distributed computing and storage through the development and study of a software-abstraction layer that interfaces to multiple Grid middleware and to new Cloud environments. Through this abstraction it is possible to sustain uninterrupted access to resources that is robust to the dynamic nature of those resources (compute nodes may fail, storage resources may go offline while a computation is being performed). We studied the software-abstraction layer and provided our Universal Grid User Interface (UGI) architecture for multiple kinds of Grid and Cloud middleware to support end users and application engineers. UGI is implemented based on A Simple API for Grid Applications (SAGA) and provides supplemental and extended functions that are not included in SAGA. We demonstrated that job submissions can be executed in the UGI-based user environment with different Grid resources. We provided and verified a simple way to execute the jobs based on High Energy and Nuclear Physics (HENP) libraries. For file manipulation, we demonstrated that an application can access the different file-system middleware in the Data Grids. The application enables to handle pieces as completed files, even if a large file is cut up and the separated parts are stored on different Data Grids. We managed the files distributed in heterogeneous Data Grids by using a catalog service. The example demonstrated that an application can obtain the location information about the pieces of files distributed among different kinds of Data Grids, and then access the distributed files. For applied tools and applications, we demonstrated a method to reliably manage files with Resource Namespace Service (RNS), a UGI-based Web application for Particle Therapy Simulation (PTSim), and an approach inspired by Ant Colony Optimization (ACO). Our method for reliably managing large files works on different kinds of Data Grids using RNS. The volume of digital data and the size of an individual file are increasing due to the introduction of high-resolution images, high-definition audiovisual files, etc. The reliable storage of such large files is becoming problematic with whole file replication as a failure in the integrity of the file is difficult to localize. Our method involves managing large files in Data Grids by splitting them into smaller units in a traceable manner and then managing the smaller units. The RNS catalog service contains EPR (Endpoint Reference) and metadata that describe the original locations as well as the checksum values. The example we shows how our Grid application can retrieve the actual file locations and the checksum values from the RNS service. Our second tool is a UGI-based Web application for PTSim. PTSim is a simulation system for particle therapy. The application of particle physics to the medical environment is one of the application areas that have a direct benefit to mankind. PTSim makes use of the Geant4 toolkit to simulate the passage of particles through the human body. It includes a Web interface that can be used by several collaborating medical particle therapy centers. The Web interface allows a non-Grid environment to be easily ported to Grid to take advantage of the additional resources. Our last tool is for an approach inspired by swarm intelligence, ACO. Swarm intelligence is one of approaches to provide a fault tolerant and efficient means of transferring data in a dynamic environment. Swarm intelligence is inspired primarily by observations of the collective behavior of social insects in addressing complex distributed problems. The basic idea is that each member of the swarm has simple rules that govern its behavior, but the interaction among the members of the swarm can be used to tackle problems that are difficult to solve with complicated numeric methods. We investigate the problem of data distribution among a client and servers in a dynamic environment. We regard each download from a server to the client as a single member in a swarm. The member’s behavior is simply to reliably download a data file. Each member can communicate with other members to allow the swarm to settle on the best set of servers to download the data from based on the current status of the environment. ACO is one of Swarm intelligence methods. We created a simulator following the ACO based approach and showed that our approach works well, providing a fault tolerant and efficient means of transferring data in a dynamic environment. We can utilize the computing and storage resources with our implementation and solution. The challenges of today’s researchers who need to collaborate with geographically distributed colleagues with distributed computing and storage resources can be overcome. |
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| 値 | 有 | |||||||
