@inproceedings{dc8cb49ba73d40659f0f00d38c0fd156,
title = "Kalman filter-based heavy hadoop job detection method for energy efficient hybrid electro-optical intra-data center networks",
abstract = "This paper proposes Hadoop job detection method using the Kalman filter and network configuration procedure for hybrid electro-optical intra-data center networks. The simulation results show improvement of detection accuracy and energy saving effect.",
author = "Masaki Murakami and Nicolas Dubrana and Yoshihiko Uematsu and Satoru Okamoto and Naoaki Yamanaka",
note = "Funding Information: This work is supported by “HOLST (High-speed Optical Layer 1 Switch system for Time slot switching optical data center networks) Project” funded by NEDO of Japan Funding Information: This work is supported by ?HOLST (High-speed Optical Layer 1 Switch system for Time slot switching based optical data center networks) Project? funded by NEDO of Japan Publisher Copyright: {\textcopyright} OSA 2021, {\textcopyright} 2021 The Author(s); 26th Optoelectronics and Communications Conference, OECC 2021 ; Conference date: 03-07-2021 Through 07-07-2021",
year = "2021",
language = "English",
series = "Optics InfoBase Conference Papers",
publisher = "The Optical Society",
booktitle = "Optoelectronics and Communications Conference, OECC 2021",
address = "United States",
}