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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| OCS, LQE, OPE | 2023-10-19 10:30 |
Kochi | (Primary: On-site, Secondary: Online) |
Study on Optical Aggregation of SP-PAM4 Signals into DP-QPSK Signal Using PM-HNLF Yuto Fujihara, Daisuke Hisano, Akihiro Maruta, Ken Mishina (Osaka Univ.)  OCS2023-26 OPE2023-81 LQE2023-28 |
All-optical modulation format conversions and signal aggregation/de-aggregations have been proposed as techniques to con... [more] | OCS2023-26 OPE2023-81 LQE2023-28 pp.1-6 |
| IN, NS (Joint) |
2023-03-03 10:10 |
Okinawa | Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
Placing Contents with Reducing FIB Size and Improving Network Quality in NDN Hiroki Hashimoto, Noriaki Kamiyama (Ritsumeikan Univ) IN2022-105 |
In recent years, Information-centric networking (ICN) has attracted wide attention as a new network architecture which c... [more] | IN2022-105 pp.235-240 |
| RCS, SR, SRW (Joint) |
2023-03-01 11:15 |
Tokyo | Tokyo Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
Self-Superviced Non-IID Federated Learning by using CKA Li Zhaojie, Ohtsuki Tomoaki (Keio Univ.), Gui Guan (NJUPT) RCS2022-254 |
Federated Learning is now widely used to train neural networks on distributed datasets. It allows a system to perform di... [more] | RCS2022-254 pp.42-47 |
| RCS, SR, SRW (Joint) |
2023-03-02 10:50 |
Tokyo | Tokyo Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
Precoder Optimization Using Correlation among Data for Wireless Data Aggregation Naoyuki Hayashi, Ayano Nakai-Kasai, Tadashi Wadayama (NIT) RCS2022-273 |
In this paper, we discuss precoder optimization in wireless data aggregation. Formulate the problem of minimizing the ... [more] |
RCS2022-273 pp.149-154 |
| CAS, MSS, IPSJ-AL [detail] | 2022-11-18 13:05 |
Kochi | (Primary: On-site, Secondary: Online) |
An Analysis of Model Parameters Propagation over Decentralized Federated Learning Koshi Eguchi, Hideya Ochiai, Hiroshi Esaki (Univ. Tokyo) CAS2022-51 MSS2022-34 |
Although there have been many studies on Decentralized Federated Learning (DFL), few have focused on the propagation of ... [more] | CAS2022-51 MSS2022-34 pp.67-70 |
| PN | 2022-11-08 11:25 |
Kochi | (Primary: On-site, Secondary: Online) |
Data aggregation technique for high-frequency band migration using chromatic dispersion control Masayuki Makino, Tomoki Tsuji (Osaka Univ.), Junya Nishioka, Seiki Nakamura, Takatoshi Akamatsu, Yoshiaki Konishi, Naoki Suzuki (MELCO), Tsuyoshi Konishi (Osaka Univ.) PN2022-29 |
We have proposed a frequency band migration technology from the low-frequency of the MHz band to the high-frequency of t... [more] | PN2022-29 pp.44-47 |
| PRMU | 2022-09-14 11:00 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Disease and severity classification of coffee leaf images by global low-level feature aggregation network Takuhiro Okada, Satoshi Iizuka, Kazuhiro Fukui (Univ. of Tsukuba) PRMU2022-14 |
Coffee leaf disease is one of the most important problems in coffee production. It is very important in the coffee produ... [more] | PRMU2022-14 pp.25-30 |
| NS, IN, CS, NV (Joint) |
2022-09-01 13:50 |
Iwate | MALIOS (Iwate Prefecture) + Online Meeting (Primary: On-site, Secondary: Online) |
Network Structure for Micro Disaggregated Data Centers Masashi Sorimachi, Akishige Ikoma, Yuichi Oshita, Masayuki Murata (Osaka Univ.) IN2022-29 |
Micro data centers (????DCs), which are small data centers located close to users, have been proposed to execute time-se... [more] | IN2022-29 pp.13-18 |
| SeMI | 2022-01-20 15:00 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
Evaluation of Few Round Training with Distillation-Based Semi-Supervised Federated Learning Yuki Yoshida (Tokyo Tech), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech) SeMI2021-65 |
This paper studies how to reduce the number of rounds in model training using Distillation-based Semi-supervised federat... [more] | SeMI2021-65 pp.48-50 |
| SeMI | 2022-01-21 15:30 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
NLN: Name-based Learning Network Towards Efficient Distributed Machine Learning Tomoki Hirayama, Li Ruidong (Kanazawa Univ.) SeMI2021-58 |
With the increase in network traffic and the number of connected devices, future networks have recently been investigate... [more] | SeMI2021-58 pp.26-29 |
| NS | 2021-10-07 16:10 |
Online | Online | An Evaluation of Multipath Tunneling using P4 Hiroaki Motohashi, Kien Nguyen, Hiroo Sekiya (Chiba Univ.) NS2021-74 |
Recently, a multipath tunneling technique has been proposed to improve the throughput of communication over the tunnels.... [more] | NS2021-74 pp.33-38 |
| CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] | 2021-01-26 09:00 |
Online | Online | Acceleration of Database Query Processing Using FPGA Hirohiko Ozaku (UEC), Masato Yoshimi (TIS), Celimuge Wu, Tsutomu Yoshinaga (UEC) VLD2020-55 CPSY2020-38 RECONF2020-74 |
A bottleneck of Big data analysis is a time to transfer large amount of data to the main memory from the storage. The da... [more] | VLD2020-55 CPSY2020-38 RECONF2020-74 pp.90-95 |
| NS, IN (Joint) |
2020-03-06 11:40 |
Okinawa | Royal Hotel Okinawa Zanpa-Misaki (Cancelled but technical report was issued) |
Traffic Flow Statistics Estimation Method by Flow De-Aggregation for SDN Data-Plane Verification Takahiro Shimizu, Naoya Kitagawa, Nariyoshi Yamai (TUAT) IN2019-127 |
Software Designed Network (SDN) is vulnerable to attacks by compromised switches because software switches commonly used... [more] | IN2019-127 pp.291-296 |
| IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] | 2020-01-23 15:25 |
Kanagawa | Raiosha, Hiyoshi Campus, Keio University | FPGA-based Stream Data Aggregation for Large Sliding-Windows Masaki Osaka (UEC), Masato Yoshimi (TIS), Celimuge Wu, Tsutomu Yoshinaga (UEC) VLD2019-76 CPSY2019-74 RECONF2019-66 |
This paper proposes an FPGA-based Stream Data Aggregation for large Sliding-Windows. We designed Configurable Query Proc... [more] | VLD2019-76 CPSY2019-74 RECONF2019-66 pp.141-146 |
| CQ | 2019-08-27 09:50 |
Hokkaido | Hakodate arena | An Approximation of Average Latency for Constant Number Data Aggregation and Adaptive Control Based on Its Characteristics Hideaki Yoshino, Yuta Okuzawa, Ryunosuke Sugihara, Kenko Ota, Takefumi Hiraguri (NIT) CQ2019-58 |
To realize latency-critical IoT applications, latency should be minimized at IoT gateways that aggregate spatially distr... [more] | CQ2019-58 pp.7-12 |
| RCS, NS (Joint) |
2018-12-21 10:50 |
Hiroshima | Onomichi City Hall | New Algorithm for Minimum Energy-cost Aggregation Tree Problem in WSNs Hiroshi Matsuura (NTT) NS2018-172 |
The MECAT (Minimum Energy-Cost Aggregation Tree) problem is for minimizing the total energy consumption of the sensors o... [more] | NS2018-172 pp.77-82 |
| WBS, ITS, RCC | 2018-12-06 13:00 |
Okinawa | Miyako Island Hirara Port Terminal Bldg. | [Poster Presentation]
Belief Propagation Analysis for Synchronization over Sensor Network Ryosuke Adachi, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) WBS2018-52 ITS2018-35 RCC2018-83 |
In this paper, distributed estimation method with optimal aggregation based on belief propagation is proposed. In the se... [more] | WBS2018-52 ITS2018-35 RCC2018-83 pp.135-139 |
| CQ, ICM, NS, NV (Joint) |
2018-11-15 11:20 |
Ishikawa | Characteristic Evaluation of Adaptive Control of Sensor Data Aggregation to Minimize Latency Hideaki Yoshino, Kenko Ota, Takefumi Hiraguri (NIT) CQ2018-68 |
In Internet of Things (IoT) systems utilizing a large amount of small-sized data, a data aggregation function, which hie... [more] | CQ2018-68 pp.27-32 |
|
| CQ | 2018-08-24 11:05 |
Shiga | Ritsumeikan Univ. Biwako-Kusatsu Campus (BKC) | System Time Characteristics and Optimal Aggregation Number of Non-statistical Data Aggregation Scheme Hideaki Yoshino, Kenko Ota, Takefumi Hiraguri (NIT) CQ2018-55 |
In IoT systems utilizing a large amount of small-sized sensor data, a data aggregation function, which summarizes spatia... [more] | CQ2018-55 pp.53-58 |
| CQ, MVE, IE, IMQ (Joint) [detail] |
2018-03-09 11:40 |
Okinawa | Okinawa Industry Support Center | System Time Characteristics and Optimization of Fundamental Data Aggregation Schemes Hideaki Yoshino, Kenko Ota, Takefumi Hiraguri (NIT) CQ2017-122 |
In Internet of Things (IoT) systems utilizing a large amount of small-sized data, a data aggregation function, which hie... [more] | CQ2017-122 pp.111-116 |
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