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As data volumes explode, data storage costs become a large fraction of total IT costs. We can reduce the costs substantially by using compression. However, it is generally known that database compression is not suitable for write-intensive workloads. In this paper, we provide a comprehensive solution to improve the performance of compressed databases for write-intensive OLTP workloads. We find that storing data too densely in compressed pages incurs many future page splits, which require exclusive locks. In order to avoid lock contention, we reduce page splits by sacrificing a couple of percent of space savings. We reserve enough space in each compressed page for future updates of records and prevent page merges that are prone to incur page splits in the near future. The experimental results using TPC-C benchmark and /InnoDB show that our method gives 1.5 times higher throughput with 33% space savings compared with the uncompressed counterpart and 1.8 times higher throughput with only 1% more space compared with the state-of-the-art compression method developed by Facebook.

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Researchers collect data and use various methods to organize it. Ensuring the reliability and reproducibility of data is crucial, and collaboration across different research fields is on the rise. However, when there is geographical distance, sharing data becomes a challenging task. Therefore, there is a need for the development of a mechanism for sharing data on the web. We have developed an integrated database to facilitate the sharing and management of research data, particularly focusing on small molecules. The integrated database serves as a platform for centralizing data related to small molecules, including their chemical structures, wet lab experimental data, simulation data, and more. It has been constructed as a web application, offering features such as library management for small molecules, registration and viewing of wet lab experiment results, generation of initial conformations for simulations, and data visualization. This enables researchers to efficiently share their research data and collaborate seamlessly, whether within their research group or via cloud-based access that allows project and team members to connect from anywhere. This integrated database plays a critical role in connecting wet lab experiments and simulations, enabling researchers to cross-reference and analyze experimental data comprehensively. It serves as an essential tool to advance research and foster idea generation.

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　本論文では, 時間変化をアニメーションによって可視化するソフトウェアの開発についての設計と実装, そしてこのソフトウェアを利用した分析結果について述べる. 分析したデータは, 経営科学系研究部会連合協議会が主催する平成25年度データ解析コンペティションで提供されたスキャンパネルデータである. このデータの購買情報とその時間に注目して, モニタの性別と年代, そして購入先について集計を行う. この結果を, 拡張した平行座標プロットによって表示し, 時間変化はアニメーションによって可視化した. この結果から, いくつかの商品についての特徴を述べる. われわれのソフトウェアでは, アニメーションだけでなく, 静止画でも変化の方向と変化量が分かるように軌跡も描く. このようなソフトウェアをJava言語とを利用して実装した.

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In infrastructure-as-a-service platforms, cloud users can adjust their database (DB) service scale to dynamic workloads by changing the number of virtual machines running a DB management system (DBMS), called DBMS instances. Replicating a DBMS instance is a non-trivial task since DBMS replication is time-consuming due to the trend that cloud vendors offer high-spec DBMS instances. This paper presents BalenaDB, which performs urgent DBMS replication for handling sudden workload increases. Unlike convectional replication schemes that implicitly assume DBMS replicas are generated on remote machines, BalenaDB generates a warmed-up DBMS replica on an instance running on the local machine where the master DBMS instance runs, by leveraging the master DBMS resources. We prototyped BalenaDB on

5.6.21, Linux 3.17.2, and Xen 4.4.1. The experimental results show that the time for generating the warmed-up DBMS replica instance on BalenaDB is up to 30× shorter than an existing DBMS instance replication scheme, achieving significantly efficient memory utilization.

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　本論文では, 購買情報の時間変化をアニメーションを利用して可視化するソフトウェアを提案し, そのソフトウェアによって表示される購買傾向について述べる. 分析したデータは, 経営科学系研究部会連合協議会が主催する, 平成26年度データ解析コンペティションにおいて提供された購買履歴である. このソフトウェアでは, グループ分けしたデータにおいて, 購買時刻に注目した集計を行い, ヒストグラムと平行座標プロットで表示する. これらの図をアニメーションによって, 表示する時間を切り替えることで, 時間変化を表す. アニメーションによる表示は, 表示している時間の変化は分かりやすいが, 全期間内での変化が分かりにくい. そこで, 全期間での変化や静止画でも変化が分かるような表示も行った. このようなソフトウェアをJava言語とを利用して実装した.

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Containers offer a lightweight alternative over virtual machines and become a preferable choice for application consolidation in the clouds. However, the sharing of kernel components can violate the I/O performance and isolation in containers. It is widely recognized that file system journaling has terrible performance side effects in containers, especially when consolidating database management systems (DBMSs). The sharing of journaling modules among containers causes performance dependency among them. This dependency violates resource consumption enforced by the resource controller, and degrades I/O performance due to the contention of the journaling module. The operating system developers have been working on novel designs of file systems or new journaling mechanisms to solve the journaling problems. This paper shows that it is possible to overcome journaling problems without re-designing file systems or implementing a new journaling method. A careful configuration of containers in existing file systems can gracefully solve the problems. Our recommended configuration consists of 1) per-container journaling by presenting each container with a virtual block device to have its own journaling module, and 2) accounting journaling I/Os separately for each container. Our experimental results show that our configuration resolves journaling-related problems, improves

performance by 3.4x, and achieves reasonable performance isolation among containers.

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Reboot-based recovery is a simple but powerful method to recover applications from failures and unstable states. Reboot-based recovery faces a challenge to apply it to a new type of applications, in-memory databases (DBs). Unlike legacy applications, since rebooting in-memory DBs loses memory objects including key-value pairs and DB blocks, it is required to restore them, causing severe performance degradation after the reboot. This paper presents an approach that allows us to perform reboot-based recovery of in-memory DBs with lower performance degradation. Our key insight is to decouple data content objects from all the memory objects. Our approach treats data items as data content objects, preserves data content objects on memory across reboots, and enforces restarted in-memory DBs to attach them. To show the effectiveness of our approach, we elaborate the idea into two real-world DBs, MyRocks and memcached. The prototypes successfully mitigate performance degradation after their reboot-based recovery.

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E-Defense is developing a system which enables all earthquake engineering researchers to freely access to valuable experimental data obtained during shake table tests executed there after some period. EDgrid is a cyberinfrastructure being developed for this purpose by using the cutting-edge information technology with NEESit in the United States of America. In this research, a data model has been developed for storing all the data related to experiments performed at E-Defense in the EDgrid central repository correctly, effectively and efficiently. The data model was developed on the basis of the event-based relational data model theory to correspond to possible future facility expansion and collaboration with other databases in various countries.

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E-Defense では, 貴重な震動台実験データを実験終了一定期間後には, 広く地震工学研究者らに公開して利用できる仕組みを構築することとしている. EDgrid はそのために構築する最新のIT 技術を駆使したサイバーインフラストラクチャであり, 米国のNEESit と協調的に進められている. 本研究では, EDgrid のセントラルリポジトリに実験に関するデータを正確かつ効率的, 効果的に貯蔵する為のデータモデルを構築した. 本データモデルは, 特に今後の諸設備の拡張, 更新や諸外国のデータベースとの連携を意識して, イベントに基づくリレーショナルデータモデルを基礎として構築した.

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SQLはRDBMSにおいてデータの操作や定義を行うためのデータベース言語であり、SQLのJOIN命令とは複数のテーブルやビューを結合してデータを一度に扱えるようにすることである。しかし現状のJOIN命令では同じホストの同じDB内のテーブル同士でしか、結合することができない。本研究では、別のホスト、別のDBからのテーブル結合をユニバーサルに実現する機能をPHPのファンクションとして作成する。システムの構成としてDBに,サーバサイド・スクリプト言語にPHPを利用した。

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現在，短納期，コスト削減，開発労力の削減などの理由から，複数のオープンソースコンポーネントを結合したオープンソースソリューションの利用が拡大している．オープンソースソリューションは，複数のオープンソースソフトウェアから構成されているため，品質の面で総体的な問題となることが多く，1つの主要コンポーネントが全体のオープンソースソリューションとしての機能自体を崩壊させる危険性も含んでいる．本論文では，こうしたオープンソースソリューションに対するソフトウェア·サービス性能評価のための確率微分方程式モデルを構築する．さらに，実際のOSSのソフトウェアフォールト発見数データに対する数値例を示す．

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The verification test of machine diagnosis techniques was carried out by Japan Power Engineering and inspection Corporation, and a system called as the RET (Residual Life Evaluation of Thermal Power Plants) system was developed as the result of this activity. The RET system can evaluate the primary damage of equipments in boiler or turbine using several residual life evaluation methods. The RET system provides valuable function for the residual life evaluation. However, this system is not necessarily utilized widely. In this study, online version of the RET system is developed for the purpose of populization of the RET system. The online RET system can evaluate the primary damage of the equipments in boiler or turbine without any extra application, and is easy to reflect new information.

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Database management systems (DBMSs) are a common service in the cloud. Cloud providers employ virtualization to consolidate DBMSs for efficient resource utilization and to isolate collocated DBMS workloads. To guarantee the service-level agreement (SLA), the disk I/O performance and its isolation are critical in DBMSs because they are inherently disk I/O intensive. This paper investigates the disk I/O performance and its isolation of

on two major virtualization platforms, KVM and LXC. KVM provides the hypervisor-based virtualization (virtual machines) while LXC provides the operating-system-level virtualization (containers). Containers are widely believed to outperform virtual machines because of negligible virtualization overheads, while virtual machines are to provide stronger performance isolation. Contrary to the general belief, our results show that KVM outperforms LXC by up to 95% in throughput without compromising the isolation. Furthermore, LXC violates the performance isolation; a container given 30% share of the disk bandwidth consumes the 70% share. Our analysis reveals that the file system journaling, which is mandatory to maintain file system consistency, has negative impact on both the performance and its isolation in the container. Because of the sharing of the journaling module in containers, the journaling activities are serialized and bundled with each other, resulting in poor performance and violation of the performance isolation.

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Recent researches have shown the possibility of accelerating traditional database with FPGAs by implementing specific query processors. In this paper, we present a method to improve hardware design productivity. First, we employ the C-based HLS to reduce the processor design cost. Second, we combine the proposed processor with a novel FPGA framework, which provides pre-developed PCIe module to reduce the system design cost. At last, we integrate the proposed data filtering processor with

database as a case study to show the development efficiency and system performance.

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We do not have the teaching staff room in our school. So, it is not easy to share data of absentees or latecomer in a few days. To solve this, I made this system with HTML, and PHP on our Web server. By using this system we became possible to share absentees and latecomers information easily.

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A GIS for ocean data applications named "Ocean Data and Information Systems (ODIS)" was designed and developed. The system is based on the University of Minnesota MapServer, an open source platform for publishing spatial data and interactive mapping applications to the web with as the backend database server. This paper discusses some of the details of the storage and organization of oceanographic data, methods employed for visualization of parameter plots, and mapping of the data. ODIS is conceived to be an end-to-end system comprising acquisition of data from a variety of heterogeneous ocean platforms, processing, integration, quality control, and web-based dissemination to users for operational and research activities. ODIS provides efficient data management and potential mapping and visualization functions for oceanographic data.

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感染症流行の早期検知と予防には感染症発生動向調査事業で収集された情報の効果的な利用が不可欠である。著者らはインターネットを通じて情報還元できるデータベースシステムを開発した。本システムでは，WebサーバソフトにApacheを，DBMS（database management system）にはを使用し，PHPスクリプトとGDライブラリにより自動的にグラフィックデータを作成させた。これにより，遠隔地ユーザーの要求に従って検索された結果から，患者発生の数値データだけでなく，視覚化された地図グラフや棒グラフの自動的な表示・提供が可能となった。また，流行の警報・注意報発令の提供も試みた。感染症の流行現象の早期把握を目的として，流行の時間的・位置的推移をインターネットのホームページ上にSVG（Scalable Vector Graphics）を用いたアニメーションとして表示するシステムを作成した。本システムは感染症診断や予防業務に有用なシステムツールであり，情報作成のために要する膨大な人手と作業時間を軽減すると考える。

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This paper proposes SPLiT (Scalable Performance Library Tool) as the methodology to improve performance of applications on multicore processors through CPU and cache optimizations on the fly. SPLiT is designed to relieve the difficulty of the performance optimization of parallel applications on multicore processors. Therefore, all programmers have to do to benefit from SPLiT is to add a few library calls to let SPLiT know which part of the application should be analyzed. This simple but compelling optimization library contributes to enrich pervasive servers on a multicore processor, which is a strong candidate for an architecture of information appliances in the near future. SPLiT analyzes and predicts application behaviors based on CPU cycle counts and cache misses. According to the analysis and predictions, SPLiT tries to allocate processes and threads sharing data onto the same physical cores in order to enhance cache efficiency. SPLiT also tries to separate cache effective codes from the codes with more cache misses for the purpose of the avoidance of cache pollutions, which result in performance degradation. Empirical experiments assuming web applications validated the efficiency of SPLiT and the performance of the web application is improved by 26%.

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