Faculty Profiles - ISHIKAWA, Yoshiharu

Papers - ISHIKAWA, Yoshiharu

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並列データストリーム処理システムにおける内部状態共有手法の検討

徳増直紀, 杉浦健人, 石川佳治, 陸可鏡

第20回情報科学技術フォーラム (FIT 2021) 2021.8

Development of IPSJ Data Science Curriculum Standard Reviewed

Tetsuro Kakeshita, Kazuo Ishii, Yoshiharu Ishikawa, Hitoshi Matsubara, Yutaka Matsuo, Tsuyoshi Murata, Miyuki Nakano, Takako Nakatani, Haruhiko Okumura, Naoko Takahashi, Norimitsu Takahashi, Gyo Uchida, Eriko Uematsu, Satoshi Saeki and Hiroshi Kato

Proc. of Open Conference on Computers in Education (OCCE 2021 DTEL) 2021.8

Approximate Fault Tolerance for Edge Stream Processing Reviewed

Daiki Takao, Kento Sugiura, Yoshiharu Ishikawa

Proceedings of DEXA 2021 Workshops (ProTime 2021) Vol. 1479 CCIS page： 173 - 183 2021.9

Language：English Publishing type：Research paper (international conference proceedings) Publisher：Communications in Computer and Information Science

Existing distributed stream processing systems generally guarantee fault tolerance by switching to standby machines and reprocessing lost data. In edge computing environments, however, we have to duplicate each edge for this conventional approach. This duplication cost increases sharply with expansion in the system scale. To solve this problem, we propose an approach to support approximate fault tolerance without edge duplication. We focus on environmental monitoring applications and utilize the correlation between sensors. In this paper, we assume that each edge estimates missing data from the observed data and aggregates them approximately. We provide a method to estimate the outputs of failed edges taking care of the uncertainty of the processing results at each edge. Our method allows the server to continue processing without waiting for the recovery of failed edges. We also show that the validity of our method by experiments using synthetic data.

DOI： 10.1007/978-3-030-87101-7_17

Scopus

HVS: Hierarchical Graph Structure Based on Voronoi Diagrams for Solving Approximate Nearest Neighbor Search Reviewed

Kejing Lu, Yoshiharu Ishikawa, Mineichi Kudo, Chuan Xiao

Proceedings of the VLDB Endowment (PVLDB) Vol. 15 ( 2 ) page： 246 - 258 2021.10

航空オブリーク撮影データからの3Dモデル高速作成の課題とその利活用

藤原紘子, 四俣徹, 杉浦健人, 石川佳治, 神林飛志, 埋金進一, 川口章, 佐藤俊明

第30回地理情報システム学会講演論文集 2021.10

航空機オブリーク画像からの3Dモデル作成の分散並列処理による高速化

四俣徹, 藤原紘子, 佐藤俊明, 大辻典, 杉浦健人, 石川佳治, 神林飛志, 埋金進一, 川口章, 鈴鹿守俊

日本写真測量学会秋季学術講演会発表論文集 2021.10

道路ネットワーク上の軌跡データに対する圧縮索引 Invited

小出智士, 肖川, 石川佳治

情報・システムソサイエティ誌 Vol. 26 ( 3 ) page： 10 - 10 2021.11

Approximate Fault-Tolerant Data Stream Aggregation for Edge Computing Invited

Takao D., Sugiura K., Ishikawa Y.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13167 LNCS page： 233 - 244 2022

Language：Japanese Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

With the development of IoT, edge computing has been attracting attention in recent years. In edge computing, simple data processing, such as aggregation and filtering, can be performed at network edges to reduce the amount of data communication and distribute the processing load. In edge computing applications, it is important to guarantee low latency, high reliability, and fault tolerance. We are working on the solution of this problem in the context of environmental sensing applications. In this paper, we outline our approach. In the proposed method, the aggregate value of each device is calculated approximately and the fault tolerance is also guaranteed approximately even when the input data is missing due to sensor device failure or communication failure. In addition, the proposed method reduces the delay by outputting the processing result when the error guarantee satisfies the user’s requirement.

DOI： 10.1007/978-3-030-96600-3_17

Scopus

Approximate Query Processing with Error Guarantees Reviewed

Tianjia Ni, Kento Sugiura, Yoshiharu Ishikawa, Kejing Lu

Ninth International Conference on Big Data Analytics in Astronomy, Science and Engineering (BDA 2021) Vol. 13167 LNCS page： 268 - 278 2021.12

In recent years, with the increase of data and the sophistication of analysis requirements, query processing in databases has become more important. Recently, approximate query processing (AQP) was proposed for efficiently executing database queries on big data. In this research, we focus on synopsis construction on a relational database and the query technology based on it, which is called Bounded Approximate Query (BAQ) proposed in 2019. BAQ is a synopsis construction method that focuses on aggregate queries using SQL, and realizes error-guaranteed query processing by grouping the dataset into the synopsis. In this paper, we point out the limitations of queries and datasets in BAQ and based on the result of experiments, we prove that the proposed method can be applied efficiently to data wider than the original BAQ with smaller synopsis within the error guarantee.

DOI： 10.1007/978-3-030-96600-3_20

Scopus

シノプシスに基づく近似問合せ処理における誤差保証の検討

倪天嘉, 杉浦健人, 石川佳治, 陸可鏡

情報処理学会研究報告データベースシステム（DBS） Vol. 2021-DBS-174(2) page： 1 - 6 2021.12

並列データストリーム処理におけるデータベースを用いた内部状態の共有

徳増直紀, 杉浦健人, 石川佳治, 陸可鏡