KEIO RESEARCHERS INFORMATION SYSTEM

Papers 【 Display / hide 】

Papers 【 Display / hide 】

• Decentralization of Two Phase Locking based Protocols

  Nakamori T., Nemoto J., Hoshino T., Kawashima H.

  HPDC 2022 - Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2022 - Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing)     281 - 282 2022.06

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  Bamboo is a state-of-the-art concurrency control protocol based on the 2-phase locking protocol. One problem of Bamboo is that it requires transactions to fetch timestamps from a single centralized atomic counter. To replace the concentrated access to it, each transaction should generate timestamps independently. This paper proposes thread-ID method (TID), which dismisses the process of fetching timestamps entirely by assigning an ID to each thread, and transactions use the thread IDs as their timestamps. In high-contention settings, the performance of TID plummets, but proposed optimization FairTID sustains the performance. The experiments measured an improvement of up to 60% from Bamboo with the proposed method.

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• Making ROS TF Transactional.

  Yushi Ogiwara, Ayanori Yorozu, Akihisa Ohya, Hideyuki Kawashima

  ICCPS    318 - 319 2022

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• Fast Concurrency Control with Thread Activity Management beyond Backoff.

  Kosei Masumura, Takashi Hoshino, Hideyuki Kawashima

  30   552 - 561 2022

  • Access to Document (DOI)

• Fast Accurate Discovery of Tuple Inclusion Dependencies

  Shen M., Kawashima H., Saito K.

  Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022 (Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022)     246 - 251 2022

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  Inclusion dependencies (IND) is an important problem in relational database, relevant to data integration, query optimization and various data management tasks. The discovery of IND has been addressed by many studies following different strategies, while IND detection still needs improvement as the complexity and diversity of real-life data increase. Conventional IND is only for column-to-column dimension, which is not applicable to lots of data processing tasks. The concept of dependency can be expanded. Based on the understanding of the conventional IND and approximate approach FAIDA, we present our algorithm for detecting tuple IND, converting column-to-column detection to row-to-row dimension, more in line with real-world data retrieval tasks in distributed system. Through probabilistic and accurate detection and the use of multi-threading, both accuracy and performance are guaranteed and IND detection performance is taken to a new level.

  • Access to Document (DOI)

• Accelerating Concurrency Control with Active Thread Adjustment

  Masumura K., Hoshino T., Kawashima H.

  Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022 (Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022)     280 - 287 2022

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  We attempted to improve the performance of Silo, a concurrency control protocol for inmemory DataBase Management System that performs well under high-contention work-loads. Adaptive backoff is known as an effective optimization method under high-contention workloads. As a result of analyzing, we found that its efficacy lies in the non-existence of conflict events rather than in the reduction of the conflict rate, which has been considered in the past. On the basis of this analysis, we propose a method of adjusting the number of active threads. We conducted experiments comparing Cicada, another concurrency control protocol, and our method applied to Silo. The results indicate that the proposed method enabled Silo to significantly outperform. We found that cache misses are related to the performance.

  • Access to Document (DOI)

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Papers, etc., Registered in KOARA 【 Display / hide 】

Papers, etc., Registered in KOARA 【 Display / hide 】

• Real-time language model

  Kawashima, Hideyuki

  学事振興資金研究成果実績報告書 (慶應義塾大学)  2022

• Real-time data kernel for data intensive science

  Kawashima, Hideyuki

  科学研究費補助金研究成果報告書 2021

• Real-time language model

  Kawashima, Hideyuki

  学事振興資金研究成果実績報告書 (慶應義塾大学)  2021

• A study of fast consensus protocol for blockchain

  Kawashima, Hideyuki

  学事振興資金研究成果実績報告書 (慶應義塾大学)  2020

• Creation of computational dance science

  Kawashima, Hideyuki

  学事振興資金研究成果実績報告書 (慶應義塾大学)  2018

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

Research Projects of Competitive Funds, etc. 【 Display / hide 】

• 自律移動ロボットに資する迅律データシステムの創出

  2022.04

  -

  2025.03

  MEXT,JSPS, Grant-in-Aid for Scientific Research, 基盤研究(B), Principal investigator

• Real-Time Data Kernel for Data Intensive Science

  2019.04

  -

  2022.03

  MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Principal investigator

Courses Taught 【 Display / hide 】

Courses Taught 【 Display / hide 】

• MASTER SEMINAR

  2026

• DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

  2026

• ADVANCED RESEARCH(CI)

  2026

• DATA SCIENCE SPECIAL LECTURE A

  2026

• ACADEMIC PROJECT(NOVEL COMPUTING: AI AND BRAIN SCIENCE)

  2026

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