Projects

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

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.

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.

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.

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

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

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

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

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