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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 48  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP, MSS 2024-03-14
10:00
Misc. Kikai-Shinko-Kaikan Bldg. Extraction of Traffic Accident High-Risk Areas Using Deep Learning of Map Images and Grad-CAM
Kaito Arase, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2023-86 NLP2023-138
An attempt has been made to predict the traffic accident risk of each map tile image at zoom level 17 using a Convolutio... [more] MSS2023-86 NLP2023-138
pp.71-76
NS, IN
(Joint)
2024-03-01
10:45
Okinawa Okinawa Convention Center ECN Congestion Control with Gradient of Queue Length for Inter-Datacenter Gateway Proxy
Keita Aoki, Miki Yamamoto (Kansai Univ.) NS2023-211
For data replication and database synchronization, inter-DC (Data Center) communications play an important role. Inter-D... [more] NS2023-211
pp.230-235
NS, RCS
(Joint)
2023-12-15
17:10
Fukuoka Kyushu Institute of Technology Tobata campus, and Online
(Primary: On-site, Secondary: Online)
A Study of Q-drop Identification by Analyzing Receiver-Side Quality Data for Optical Transmission Systems
Kohei Watanabe, Hiroshi Yamamoto, Hiroki Date, Daisaku Shimazaki (NTT), Yutaka Fukuchi, Hideki Maeda (TUS) NS2023-153
High reliability is required for optical transmission systems, which are widely deployed as the network infrastructure f... [more] NS2023-153
pp.157-162
IA 2023-11-22
16:25
Aomori Aomori Prefecture Tourist Center ASPM (Aomori)
(Primary: On-site, Secondary: Online)
Improving the accuracy of flow prediction and anomaly detection in GAMPAL, a general-purpose anomaly detection mechanism for Internet traffic
Taku Wakui (Keio Univ./Hitachi), Fumio Teraoka (Keio Univ.), Takao Kondo (Hokkaido Univ./Keio Univ.) IA2023-41
The authors propose a general-purpose anomaly detection mechanism using Prefix Aggregate without Labeled data (GAMPAL) f... [more] IA2023-41
pp.33-40
RISING
(3rd)
2023-10-31
13:00
Hokkaido Kaderu 2・7 (Sapporo) [Poster Presentation] Few Shot Learning-Driven Traffic Forecast for 5G VNF Scaling
Qianqian Pan, Akihiro Nakao (The Univ. of Tokyo)
Virtual network functions (VNFs) make 5G networks more feasible to the diverse and heterogeneous communication environme... [more]
NS 2023-10-05
09:20
Hokkaido Hokkaidou University + Online
(Primary: On-site, Secondary: Online)
[Encouragement Talk] Experimental Evaluation of Vehicle Traffic Density Estimation for Predicting Communication Traffic Volume by Vehicle Communication Services
Yoshie Morita, Kengo Tajiri, Yoichi Matsuo (NTT) NS2023-84
Vehicle communication services using the mobile communication network would further increase communication traffic volum... [more] NS2023-84
pp.71-76
IA 2023-09-21
14:40
Hokkaido Hokkaido Univeristy
(Primary: On-site, Secondary: Online)
Extracting context from external events using auxiliary information from network traffic data
Eilaf M.A Babai, Koji Okamura (Kyushu Univ.) IA2023-13
Network traffic flow data is the main source of information about the network status, and it is constantly monitored to ... [more] IA2023-13
pp.11-18
NS 2023-04-13
13:40
Fukushima Nihon University, Koriyama Campus + Online
(Primary: On-site, Secondary: Online)
Vehicle Traffic Density Estimation for Predicting Communication Traffic Volume by Vehicle Communication Service
Yoshie Morita, Kengo Tajiri, Yoichi Matsuo (NTT) NS2023-3
Vehicle communication services are new services using the mobile communication network. Since these services are expecte... [more] NS2023-3
pp.13-18
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
CQ, CBE
(Joint)
2021-01-20
11:15
Online Online [Invited Lecture] Network control technologies based on QoS requirements
Masahiro Kobayashi, Shigeaki Harada (NTT) CQ2020-64
With the development of virtualization technologies such as Software-Defined Networking (SDN) and Network Functions Virt... [more] CQ2020-64
pp.22-26
NS, IN
(Joint)
2020-03-06
13:20
Okinawa Royal Hotel Okinawa Zanpa-Misaki
(Cancelled but technical report was issued)
Relearning Mechanism to Follow Trend Changes for Resource Arbitration in NFV Platforms
Takahiro HIrayama, Mashiro Jibiki, Ved P. Kafle (NICT) IN2019-137
Network Function Virtualization (NFV) provides diverse virtualized functions for services such as Internet-of-Things (Io... [more] IN2019-137
pp.351-356
RCS, SR, SRW
(Joint)
2020-03-04
09:00
Tokyo Tokyo Institute of Technology
(Cancelled but technical report was issued)
R&D of Technology for High Reliability Management of Advanced 5G Network to Various Requirements of Communication Services
Takahide Murakami, Hiroyuki Shinbo, Yu Tsukamoto, Shinobu Nanba, Yoji Kishi (KDDI Research), Morihiko Tamai, Hiroyuki Yokoyama (ATR), Takanori Hara, Koji Ishibashi (The University of Electro-Communications), Kensuke Tsuda, Yoshimi Fujii (Kozo Keikaku Engineering Inc.), Fumiyuki Adachi, Keisuke Kasai, Masataka Nakazawa (Tohoku Univ.), Yuta Seki, Takayuki Sotoyama (Panasonic) RCS2019-320
As the 5th generation mobile communication system is widespread approximately 2025, more variety of communication qualit... [more] RCS2019-320
pp.1-6
CS, CAS 2020-02-27
14:30
Kumamoto   An Estimation of Network Traffic Validation based on Sparse Coding
Takayuki Nakachi, Yitu Wang (NTT) CAS2019-107 CS2019-107
With accurate network traffic prediction, future communication networks can realize self-management and enjoy intelligen... [more] CAS2019-107 CS2019-107
pp.55-60
RISING
(2nd)
2019-11-27
13:55
Tokyo Fukutake Learning Theater, Hongo Campus, Univ. Tokyo [Poster Presentation] Resource Allocation Incorporating Real-World Information For Network Slices With Human Brain Cognition
Semin An, Yuichi Ohsita, Nasayuki Murata (Osaka Univ.)
Network slicing is a technology to accomodate various network services. By using a network slicing, we allocate resource... [more]
NS, ICM, CQ, NV
(Joint)
2019-11-21
10:45
Hyogo Rokkodai 2nd Campus, Kobe Univ. Investigation of The Effect of Using Attribute Information in Network Traffic Prediction with Deep Learning
Yusuke Tokuyama, Yukinobu Fukushima, Yuya Tarutani, Tokumi Yokohira (Okayama Univ.) NS2019-122
It is crucial for network operators to predict network traffic in the future as accurate as possible for appropriate res... [more] NS2019-122
pp.13-18
AP, RCS
(Joint)
2019-11-21
10:15
Saga Saga Univ. Study of Frequency Usage Prediction Using Machine Leaning for Spectrum Sharing
Hiroki Hosoi, Toshiyuki Maeyama (Takushoku Univ.), Tatsuya Yoshioka (ATR), Nobuo Suzuki (Kindai Univ.) RCS2019-216
Recently, traffic has been increasing rapidly, there is concern about the depletion of frequency resources. For this rea... [more] RCS2019-216
pp.79-84
SR
(2nd)
2019-11-04
- 2019-11-05
Overseas Rutgers University Inn & Conference Center, NJ, USA Traffic Prediction in Future Mobile Networks using Hidden Markov Model
Sumeet Dash (Shiv Nadir Univ.), Sumit Maheshwari (Rutgers Univ.), Sudipta Mahapatra (IIT Kharagpur)
The recent advances in the wireless network architectures are mainly focused on improving the end-user performance as me... [more]
AP 2019-10-18
13:00
Osaka Osaka Univ. A study on variety and size of input data for radio propagation prediction using a deep neural network
Takahiro Hayashi, Tatsuya Nagao, Satoshi Ito (KDDI Research, Inc) AP2019-102
Not only has the volume of mobile traffic been increasing exponentially in recent years, making various services availab... [more] AP2019-102
pp.119-124
RCS, SAT
(Joint)
2019-08-23
11:45
Aichi Nagoya University Wireless Network Control Enabled by Data Assessment Using Machine Learning
Ryoichi Shinkuma, Takayuki Nishio (Kyoto Univ.) RCS2019-166
The real-time prediction of spatial information is promising for next-generation mobile networks. Recent developments in... [more] RCS2019-166
pp.109-112
CQ, ICM, NS, NV
(Joint)
2018-11-16
11:30
Ishikawa   Prediction of Variation in Network Traffic by RNN
Haruka Osanai (Ochanomizu Univ.), Akihiro Nakao, Shu Yamamoto (Univ. of Tokyo), Saneyasu Yamaguchi (Kogakuin Univ.), Masato Oguchi (Ochanomizu Univ.) NS2018-145
A network congestion is caused by large scale disasters, multiple OSes upgrades which happen simultaneously, DDoS attack... [more] NS2018-145
pp.87-92
 Results 1 - 20 of 48  /  [Next]  
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