activity
20022026
most citedAnomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization

9 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2026

Contextual Bandit-Based Decomposition of Network Slice Requirements under Cumulative Resource Budget Constraints

Masaki Kobayashi, Akito Suzuki, Ryoichi Kawahara +1

End-to-end (E2E) network slices (NSs) are provisioned across multiple domains of the 5G network. In hierarchical NS management, a tenant submits a network slice request (NSR), whic…

cs.DC2019

Extendable NFV-Integrated Control Method Using Reinforcement Learning

Akito Suzuki, Ryoichi Kawahara, Masahiro Kobayashi +3

Network functions virtualization (NFV) enables telecommunications service providers to realize various network services by flexibly combining multiple virtual network functions (VN…

stat.ML2018★ 9 cited

Anomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization

Yasuhiro Ikeda, Keisuke Ishibashi, Yuusuke Nakano +2

Automated anomaly detection is essential for managing information and communications technology (ICT) systems to maintain reliable services with minimum burden on operators. For de…

cs.PF2014

Theoretical Evaluation of Offloading through Wireless LANs

Hiroshi Saito, Ryoichi Kawahara

Offloading of cellular traffic through a wireless local area network (WLAN) is theoretically evaluated. First, empirical data sets of the locations of WLAN internet access points a…

cs.NI2002★ 1 cited

Analysis of Non-Gaussian Nature of Network Traffic and its Implication on Network Performance

Tatsuya Mori, Ryoichi Kawahara, Shozo Naito

We analyzed the non-Gaussian nature of network traffic using some Internet traffic data. We found that (1) the non-Gaussian nature degrades network performance, (2) it is caused by…

cs.NI2002

Analysis of Non-Gaussian Nature of Network Traffic

Tatsuya Mori, Ryoichi Kawahara, Shozo Naito

To study mechanisms that cause the non-Gaussian nature of network traffic, we analyzed IP flow statistics. For greedy flows in particular, we investigated the hop counts between so…