Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NS, IN (Joint) |
2024-02-29 10:10 |
Okinawa |
Okinawa Convention Center |
Analysis of Wireless Link for Mobile Communication Devices Using a Machine Learning Model Yuki Kanto, Kohei Watabe (Nagaoka Univ. of Tech.) IN2023-67 |
In recent years, mobile communication devices have been providing various services via high-speed and high-capacity wire... [more] |
IN2023-67 pp.13-18 |
MIKA (3rd) |
2023-10-10 15:35 |
Okinawa |
Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Study on the Information Diffusion via Reposts without Explicit Diffusion Paths on Social Media Yuto Tamura, Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (NUT) |
The spread of information on social media can be understood as a process where one receives information from those they ... [more] |
|
CQ, MIKA (Joint) (2nd) |
2023-08-30 16:20 |
Fukushima |
Tenjin-Misaki Sports Park |
[Poster Presentation]
Analysis of occurrence patterns in retweets without explicit diffusion paths focusing on the distance between users Yuto Tamura, Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (NUT) |
On social media, it is conceivable that information diffusion is facilitated by the recurrent actions of users who engag... [more] |
|
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 10:35 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Evaluation of the effectiveness of link deletion based on diffusion prediction for suppressing information diffusion on social media Shiori Furukawa, Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (Nagaoka Univ. of Tech) CQ2022-82 |
[more] |
CQ2022-82 pp.13-18 |
IN |
2023-01-19 10:00 |
Aichi |
Aichi Industry & Labor Center (Primary: On-site, Secondary: Online) |
A Learning-Based Accurate Graph Reconstruction Model with Deep Learning Takahiro Yokoyama, Yoshiki Sato (Nagaoka Univ. of Tech.), Sho Tsugawa (Univ. Tsukuba), Kohei Watabe (Nagaoka Univ. of Tech.) IN2022-52 |
In recent years, there has been an increasing interest in developing models for learning and generating graphs using dee... [more] |
IN2022-52 pp.1-6 |
IN |
2023-01-19 10:25 |
Aichi |
Aichi Industry & Labor Center (Primary: On-site, Secondary: Online) |
Flow Classification Using Flow Collections and Deep Learning Loc Gia Nguyen, Kohei Watabe (Nagaoka Univ. of Tech.) IN2022-53 |
This study aims to explore the possibility of using collections of flows to improve classification accuracy of network f... [more] |
IN2022-53 pp.7-12 |
IN, CCS (Joint) |
2022-08-05 09:40 |
Hokkaido |
Hokkaido University(Centennial Hall) (Primary: On-site, Secondary: Online) |
Machine Learning-Based Network Traffic Prediction with Tunable Parameters Kaito Kuriyama, Kohei Watabe (Nagaoka Univ. of Tech.) IN2022-20 |
Network evaluation has become increasingly important in recent years.
Network evaluation requires large amounts of traf... [more] |
IN2022-20 pp.27-32 |
SAT, SANE (Joint) |
2022-02-25 09:30 |
Online |
Online |
Bandwidth and Power Allocation for a Multi-beam Satellite Communication System in the Japanese Islands Shun Okuhama (ONCT), Kohei Watabe (NUT), Katsuya Nakahira (ONCT) SAT2021-62 |
Multi-beam systems have become the mainstream for satellite communications because they can make effective use of freque... [more] |
SAT2021-62 pp.57-61 |
CQ, CBE (Joint) |
2022-01-28 14:40 |
Ishikawa |
Kanazawa(Ishikawa Pref.) (Primary: On-site, Secondary: Online) |
A Study on Finding Intermediate Spreaders in Social Networks Sho Tsugawa (Univ. of Tsukuba), Kohei Watabe (Nagaoka Univ. of Technology) CQ2021-94 |
Identifying influencers in a given social network has been an important research problem. In the literature, several me... [more] |
CQ2021-94 pp.100-105 |
IN, NS (Joint) |
2021-03-05 14:20 |
Online |
Online |
A study of a tunable generative model for graph data using machine learning Shohei Nakazawa, Yoshiki Sato, Kenji Nakagawa (Nagaoka Univ. of Tech.), Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (Nagaoka Univ. of Tech.) NS2020-159 |
In recent years, applications and simulations using graphs are becoming more important. The graph has various features, ... [more] |
NS2020-159 pp.214-219 |
CQ, CBE (Joint) |
2021-01-20 16:05 |
Online |
Online |
[Invited Talk]
A machine learning approach to data generation in networks Kohei Watabe (Nagaoka Univ. of Tech.) CQ2020-71 |
When we evaluate communication networks and protocols/applications running on them, it is important to demonstrate their... [more] |
CQ2020-71 p.57 |
NS, RCS (Joint) |
2020-12-18 15:50 |
Online |
Online |
Improvement of Fairness and Throughput in Multi-Hop Wireless Ad Hoc Networks Truong Van Nhat Minh, Kenji Nakagawa, Kohei Watabe (Nagaoka Univ. of Tech) NS2020-106 |
[more] |
NS2020-106 pp.103-107 |
IN, IA (Joint) |
2019-12-20 10:45 |
Hiroshima |
Satellite Campus Hiroshima |
Packet loss rate estimation and path selection method by minimizing L1 norm in multicast communication Taiji Kichikawa, Kenji Nakagawa, Kohei Watabe (Nagaoka University of Univ.) IN2019-54 |
[more] |
IN2019-54 pp.51-55 |
IN, IA (Joint) |
2019-12-20 11:10 |
Hiroshima |
Satellite Campus Hiroshima |
Available bandwidth estimation method using MACD index Ryota Saito, Kenji Nakagawa, Kohei Watabe (Nagaoka Univ. of Tech) IN2019-55 |
In recent years, services that consume bandwidth on the Internet have become popular. In order to provide these services... [more] |
IN2019-55 pp.57-61 |
MIKA (2nd) |
2019-10-04 10:15 |
Hokkaido |
Hokkaido Univ. |
[Poster Presentation]
A study of similar network generative model using machine learning Shohei Nakazawa, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Tech.) |
A real topology data are required when we simulate assuming an environment close to a real situation. The real data of t... [more] |
|
CQ |
2019-07-18 13:00 |
Niigata |
Niigata Univ. |
[Poster Presentation]
A Study on Pseudo Traffic Generation Using Machine Learning Tetsuya Yamagiwa, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Tech.) CQ2019-38 |
When we constructing a network, it is important to use a traffic generator that generates realistic traffic and perform load... [more] |
CQ2019-38 pp.27-29 |
IN, NS (Joint) |
2019-03-05 13:50 |
Okinawa |
Okinawa Convention Center |
On Accurate Packet Loss Estimation Method for Networks without Traffic Models Masahiro Terauchi, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. Tech.) IN2018-131 |
It is important to accurately model network traffic when we evaluate Quality of Service~(QoS) of networks through simula... [more] |
IN2018-131 pp.283-288 |
IN, NS (Joint) |
2019-03-05 14:10 |
Okinawa |
Okinawa Convention Center |
Estimation of packet drop rate by parallel path active measurement Norinosuke Murai, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Technology) IN2018-132 |
In this paper, we propose a method to estimate packet drop rate by performing end-to-end multi-path active measurement o... [more] |
IN2018-132 pp.289-294 |
NS, IN (Joint) |
2018-03-02 10:00 |
Miyazaki |
Phoenix Seagaia Resort |
Estimation of Failure Locations by Path Integration/partition in Network Failure Yohsuke Tsutsumi, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Technology) NS2017-198 |
[more] |
NS2017-198 pp.175-180 |
CQ (2nd) |
2018-01-20 12:50 |
Tokyo |
Nishiwaseda Campus, Waseda Univ. |
[Poster Presentation]
A Study of a Packet Loss Estimation Using Importance Sampling in Networks with Unknown Traffic Masahiro Terauchi, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Technology) |
Techniques for measuring the packet loss probability with high accuracy are important to ensure Service Level Agreements... [more] |
|