研究プロジェクト

各個別の研究プロジェクトは以下のとおりです。キーワードを選択して、表示をフィルタリングできます。

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Design & Analysis of Software Process

ソフトウェア開発プロセス 近年,ソフトウェア開発は大規模化,複雑化の一途をたどっており,巨大なシステムの開発には数千人もの開発者,数十もの開発

NoOps (No Operation) を実現するソフトウェア開発自動化

現在編集中 しばらくお待ちください.当該テーマにご興味がある方は,sdlab-contact@is.naist.jpにご連絡ください

ソフトウェア開発を加速させるAI

現在編集中 しばらくお待ちください.当該テーマにご興味がある方は,sdlab-contact@is.naist.jpにご連絡ください

Software Repository Mining

ソフトウェア開発履歴からのお宝発掘 - リポジトリマイニング 本研究ではソフトウェア理解を支援するために,これまでに開発されたソフトウェア群の開発

Software Analytics

(現在編集中[2024年5月15日].最新研究に興味がある方はsdlab-contact@is.naist.jpにご連絡ください) ソフトウェ

Software for Cloud Computing

近年のクラウドコンピューティングの飛躍的な普及の背景には,ソフトウェア技術により計算機資源を仮想化することで,計算機環境の構築・割当を動的か

Software for High Performance Computing

概要 PC上では不可能な規模の計算を実現する高性能計算機(スーパコンピュータ)は,天気予報のように身近なところから,ビッグデータ解析や人工知能

Improving Resource Utilization of Data Center using LSTM

Improving Resource Utilization of Data Center using LSTM

Data centers are centralized facilities where computing and networking hardware are aggregated to handle large amounts of data and computation. In a data center, computing resources such as CPU and memory are usually managed by a resource manager. The resource manager accepts resource requests from users and allocates resources to their applications. A commonly known problem in resource management is that users often request more resources than their applications actually use.

Comparative performance study of lightweight hypervisors used in container environment

Virtual Machines (VMs) are used extensively in the cloud. The underlying hypervisors allow hardware resources to be split into multiple virtual units which enables server consolidation, fault containment and resource management. However, VMs with traditional architecture introduce heavy overhead and reduce application performance. Containers are becoming popular options for running applications, yet such a solution raises security concerns due to weaker isolation than VMs. We are at the point of container and traditional virtualization convergence where lightweight hypervisors are implemented and integrated into the container ecosystem in order to maximize the benefits of VM isolation and container performance.

An Interactive Monitoring Tool for OpenFlow Networks (Opimon)

An Interactive Monitoring Tool for OpenFlow Networks (Opimon)

Software Defined Network (SDN) is an another approach to networking that realizes network programmability and dynamic control over the network. OpenFlow is a de facto standard protocol used to implement an SDN. However, understanding the dynamic behavior of an OpenFlow network is challenging since the information about the operation is distributed across numerous network switches. Opimon (OpenFlow Interactive Monitoring) is developed for monitoring and visualizing the network topology and flow

Ensembling Heterogeneous Models for Federated Learning

Ensembling Heterogeneous Models for Federated Learning

Federated learning trains a model on a centralized server using datasets distributed over a large number of edge devices. Applying federated learning ensures data privacy because it does not transfer local data from edge devices to the server. Existing federated learning algorithms assume that all deployed models share the same structure. However, it is often infeasible to distribute the same model to every edge device because of hardware limitations such as computing performance and storage space.

Retraining Quantized Neural Networks without Labeled Data

Retraining Quantized Neural Networks without Labeled Data

Running neural network models on edge devices is attracting much attention by neural network researchers since edge computing technology is becoming more powerful than ever. However, deploying large neural network models on edge devices is challenging due to the limitation in available computing resources and storage space. Therefore, model compression techniques have been recently studied to reduce the model size and fit models on resource-limited edge devices. Compressing neural network models reduces the size of a model, but also degrades the accuracy of the model since it reduces the precision of weights in the model.

Federated Infrastructure for Collaborative Machine Learning on Heterogeneous Environments

Federated Infrastructure for Collaborative Machine Learning on Heterogeneous Environments

Federated learning is a technique for training machine learning models while keeping data private. The data is kept on the devices or servers where it was collected, and only updates to the model are shared between the parties involved in the training process. This approach is effective in addressing privacy concerns and allows for a diverse dataset, with data coming from multiple sources. However, resource constraints on edge devices make it difficult for all user devices to use the same model, which could impact the model’s accuracy.

Empirical Dynamic Modelingの最適化・並列化

Empirical Dynamic Modeling (EDM) は, Takensの埋め込み定理に基づく非線形時系列解析手法です. EDMは,力学系の状態変数の予測,非線形性の評価,変数間の因果分析等

In-situワークフローに関する研究

In-situワークフローに関する研究

概要 高性能計算機の演算性能は急速に拡大しているにも関わらず,ストレージの帯域幅や容量の性能向上は演算性能の向上に追従できていません.ストレー

SDNを応用した動的な相互結合網制御

SDNを応用した動的な相互結合網制御

概要 高性能計算機の多くは,複数の計算機を相互結合網と呼ばれるネットワークを介して相互接続したクラスタアーキテクチャを採用しています.クラスタ

テストコード自動推薦ツール

テストコード自動推薦ツール

開発者に高品質のテストコードを自動推薦するツールの開発に取り組んでいます.ソフトウェアの品質確保の要と言えるソフトウェアテストを支援すること

MUDABlue ソフトウェア自動分類システム

MUDABlue ソフトウェア自動分類システム

類似ソフトウェアの発見 MUDABlue はソフトウェアリポジトリに蓄積されている膨大なソフトウェアの分類を自動化するためのシステムです. MUDABlue が提供する分類結果

コードクローン履歴理解支援環境

コードクローン履歴理解支援環境

コードクローンとは ソースコード中に現れる重複コードのことをコードクローンと呼ばれています. コードクローンの多くは安易なコピー&ペース

A Hybrid Game Contents Streaming Method to Improve Graphic Quality Delivered on Cloud Gaming

Background In recent years, Cloud Gaming, also regarded as gaming on demand, is an emerging gaming service that envisions a promising future of providing million clients with novel and highly accessible gaming experiences, as it has been an active topic both in industries and research fields recently. Compared to Online Game which only stores game status, Cloud Gaming takes more advantages of cloud infrastructures by leveraging reliable, elastic and high-performance computing resources.

A Multipath Controller for Accelerating GridFTP Transfer over SDN

A Multipath Controller for Accelerating GridFTP Transfer over SDN

A large amount of scientific data needs to be transferred from one site to another as fast as possible in the computational science fields. High-speed data transfer between sites is very important, especially in the Grid computing field; GridFTP has been widely used for bulk data transfer over a wide area network. GridFTP achieves greater performance by supporting parallel TCP streams. Using parallel TCP streams improves the throughput of slow-start algorithms and lossy networks even on a single path.

Overseer: SDN-Assisted Bandwidth and Latency Aware Route Optimization based on Application Requirement

Overseer: SDN-Assisted Bandwidth and Latency Aware Route Optimization based on Application Requirement

Bandwidth and latency are two major factors that contribute the most to network application performance. Between each pair of switches in a network, there may be multiple paths connecting them. Each path has different proper- ties because of multiple factors. Traditional shortest-path routing does not take this knowledge into consideration and may result in sub-optimal performance of applications and underutilization of the network. We propose a concept of “bandwidth and latency aware routing”.

Multipath TCP routing with OpenFlow

Multipath TCP routing with OpenFlow

Multipath TCP (MPTCP) is an extension to TCP that allows multiple TCP subflows to be created from a single application socket. This is done automatically by operating system kernel implementation, such as MPTCP Kernel. MPTCP has advantages over network layer and application layer multipathing. This is because MPTCP, unlike network layer mechanisms such as Equal-Cost Multipathing (ECMP), is capable of independent congestion control on multiple paths and therefore works well in unequal networks, which is the situation of PRAGMA-ENT.

PReP(Product Relation-based Process modeling)

PReP(Product Relation-based Process modeling)

PRePはソニー株式会社と当講座およびソフトウェア工学講座の共同研究で開発された成果物指向のソフトウェアプロセスモデル化手法です. 研究背景 ソ

AQUAMarine - 定量的管理計画立案支援システム

AQUAMarine - 定量的管理計画立案支援システム

AQUAMarineとは AQUAMarine は,プロジェクト計画者による定量的管理計画の立案作業支援を目的としたシステムです.AQUAMarine は本講座が株