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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, IT, RCS | 2021-01-22 10:15 |
Online | Online | Proposal of a Method for Reducing the Amount of Calculation for Downlink Non-orthogonal Multiple Access Yohei Ishii, Toshinori Suzuki, Hideki Yoshikawa (Tohoku Gakuin Univ)  IT2020-86 SIP2020-64 RCS2020-177 |
In this paper, we propose a method to reduce the amount of calculation, which has been a problem in the conventional met... [more] | IT2020-86 SIP2020-64 RCS2020-177 pp.125-130 |
| COMP | 2020-10-23 15:40 |
Osaka | Osaka Univ. (Primary: On-site, Secondary: Online) |
Optimal online packet scheduling for 2-bounded delay buffer management with lookahead Koji M. Kobayashi (UT) COMP2020-15 |
The bounded delay buffer management problem proposed by Kesselman et~al. (STOC 2001 and SIAM Journal on Computing 33(3),... [more] | COMP2020-15 pp.26-32 |
| PN | 2020-08-25 10:50 |
Online | Online | Policy Gradient-based Deep Reinforcement Learning for Deadline-aware Data Transfer over Wide Area Networks Masaki Notoya, Kohei Shiomoto (Tokyo City Univ.), Takashi Kurimoto (NII) PN2020-21 |
Deadline-aware job scheduling problems have been attracting attention in the application domains of scientific workflows... [more] | PN2020-21 pp.49-56 |
| MSS, NLP (Joint) |
2020-03-10 17:10 |
Aichi | (Cancelled but technical report was issued) |
An Application of Deep Reinforcement Learning to Networked Control Under Communication Channel Constraints Takahiro Kozuka, Kazumune Hashimoto, Toshimitsu Ushio (Osaka Univ.) NLP2019-132 |
In this report, we consider a networked control system under channel constrains. Our purpose is to optimize both control... [more] | NLP2019-132 pp.109-113 |
| SeMI | 2020-01-31 10:00 |
Kagawa | [Poster Presentation]
Experimental Evaluation of Federated Learning in Real Networks Naoya Yoshida, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ.) SeMI2019-110 |
Federated Learning (FL) is a decentralized learning mechanism, which enables to train machine learning (ML) models using... [more] | SeMI2019-110 pp.49-50 |
|
| RISING (2nd) |
2019-11-26 14:10 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Invited Lecture]
MPTCP Packet Scheduler to Reduce Head of Line Blocking for Video Streaming Shinichi Nagayama, Dirceu Cavendish, Daiki Nobayashi, Takeshi Ikenaga (Kyutech) |
The popularization of video contents increases the amount of video traffic in the internet year by year. Most video stre... [more] | |
| SAT | 2019-10-11 15:20 |
Fukuoka | JR HAKATA CITY {10F RoomA+B} | Performance improvement of UAV-assisted data gathering system for distributed IoT terminals Kohei Ueno, Eiji Okamoto (NIT), Hiroyuki Tsuji, Amane Miura (NICT) SAT2019-63 |
In recent years, the fifth-generation mobile communications system (5G) has been considered for the realization of a sma... [more] | SAT2019-63 pp.115-120 |
| RCS | 2019-06-19 11:10 |
Okinawa | Miyakojima Hirara Port Terminal Building | An energy-efficient and wide-area uplink IoT data transmission scheme using UAV Kohei Ueno, Eiji Okamoto (NITech), Hiroyuki Tsuji, Amane Miura (NICT) RCS2019-46 |
In recent years, in the fifth generation mobile communications system (5G) has been considered to realize a smart societ... [more] | RCS2019-46 pp.55-60 |
| RCS | 2019-06-19 15:15 |
Okinawa | Miyakojima Hirara Port Terminal Building | A Study for Improving Prediction Accuracy on Federated Learning with Non-IID Data in Wireless Networks Naoya Yoshida, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ.), Ryo Yonetani (OMRON SINIC X Corp.) RCS2019-54 |
Federated Learning (FL) is a decentralized learning mechanism, which enables to train machine learning (ML) model using ... [more] | RCS2019-54 pp.103-108 |
| IA, IN (Joint) |
2018-12-14 11:35 |
Hiroshima | Hiroshima Univ. | A Proposal of MPTCP Scheduler considering one-way latency information and out-of-order under various delay conditions Yuta Kinoshita, Ismail Arai, Kazutoshi Fujikawa (NAIST) IA2018-49 |
The currently implemented MPTCP has a problem that the throughput decreases compared to normal TCP in an environment whe... [more] | IA2018-49 pp.59-63 |
| MSS, CAS, IPSJ-AL [detail] | 2018-11-13 11:00 |
Shizuoka | Study on Mid-term Planning of Radiographer Scheduling Problem Toshiyuki Miyamoto, Kuniyuki Hidaka (Osaka Univ.) CAS2018-69 MSS2018-45 |
Those who perform diagnosis and treatment of patients using medical imaging diagnostic apparatuses such as MRI and CT in... [more] | CAS2018-69 MSS2018-45 pp.89-93 |
|
| SR | 2018-10-30 10:30 |
Overseas | Mandarin Hotel, Bangkok, Thailand | [Poster Presentation]
Q-Leaning based Cell Zooming for Energy-Harvesting Small Cell Networks Katsuya Suto (UEC), Masashi Wakaiki (Kobe Univ.) SR2018-62 |
With the dense deployment of small cell base stations (SBSs), the radio access network can boost spectrum efficiency. To... [more] | SR2018-62 pp.9-10 |
| RCS, NS (Joint) |
2017-12-15 15:35 |
Hiroshima | Aster Plaza | [Encouragement Talk]
A Proposal of Scheduling to Improve QoS of Periodic Flows in Wireless Multihop Sensor Networks Anh Huy Nguyen, Yosuke Tanigawa, Hideki Tode (Osaka Prefecture Univ.) NS2017-142 |
Recently, the demand for wireless networks treating periodical traffic is increasing. However, this tendency causes the ... [more] | NS2017-142 pp.85-90 |
| MVE | 2017-09-22 10:30 |
Chiba | Chiba Univ. | Dynamic Scheduling Method of Cooking Process Considering The Finishing Temperature of Dishes Yuuki Kayahara (Ritsumeikan Univ.), Hiroaki Kuwabara (Nanzan Univ.), Yoshitoshi Kunieda (Ritsumeikan Univ.) MVE2017-21 |
When cooking two or more items, if you cook one item at a time, it takes time for the cooker to spare, so you can not co... [more] | MVE2017-21 pp.37-41 |
| NLP | 2017-03-14 10:00 |
Aomori | Nebuta Museum Warasse | Search Capability of DPSO with Dynamically Varying Gain-Parameter Nobuaki Hashimoto, Masato Kaneko, Toshiya Iwai (Nihon Univ.) NLP2016-106 |
Discrete Particle Swarm Optimization(DPSO) is a metaheuristics that is improved to apply PSO to the discrete optimizatio... [more] | NLP2016-106 pp.1-6 |
| SS | 2017-03-10 10:05 |
Okinawa | Multitask Scheduling Method for Reducing Total Heap Memory Usage under Deadline Constraints Yuto Suzuki, Akio Nakata (Hiroshima City Univ.) SS2016-76 |
Multitasking systems, often used in embedded software, require in general larger memory footprint than single tasking sy... [more] | SS2016-76 pp.97-102 |
|
| CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] | 2017-03-10 16:20 |
Okinawa | Kumejima Island | TSCH Scheduling Considering Energy Consumption in Wireless Sensor Network Tadanori Matsui, Hiroaki Nishi (Keio univ.) CPSY2016-160 DC2016-106 |
The demand for Wireless Sensor Network(WSN) has drastically increased because Internet of Things(IoT) became popular wit... [more] | CPSY2016-160 DC2016-106 pp.387-392 |
| NS, IN (Joint) |
2017-03-03 09:30 |
Okinawa | OKINAWA ZANPAMISAKI ROYAL HOTEL | Flow Discarding Method in WRR Weight Assignment Method Sho Noda, Katsunori Yamaoka (Tokyo Tech) IN2016-123 |
Our conventional method, approaching to optimal WRR weight assignment method in delay-limited environment, does not cons... [more] | IN2016-123 pp.157-162 |
| VLD, DC, CPSY, RECONF, CPM, ICD, IE (Joint) [detail] |
2016-11-28 10:55 |
Osaka | Ritsumeikan University, Osaka Ibaraki Campus | Scheduling of Malleable Fork-Join Tasks Kana Shimada, Ittetsu Taniguchi, Hiroyuki Tomiyama (Ritsumeikan Univ.) VLD2016-45 DC2016-39 |
This paper studies scheduling of malleable fork-join tasks. In our scheduling problem, each task can be partitioned into... [more] | VLD2016-45 DC2016-39 pp.7-11 |
| SR | 2016-10-28 15:05 |
Osaka | Osaka Univ. Nakanoshima Center | An initial evaluation of scheduling method for MUST with different waveforms Tatsuya Yoshioka, Hiroyuki Shinbo (ATR) SR2016-75 |
The 5th generation mobile communication systems need to accommodate various user’s traffic effectively with limited freq... [more] | SR2016-75 pp.115-120 |
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