Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks

Masaki Murakami; Nicolas Dubrana; Yoshihiko Uematsu; Satoru Okamoto; Naoaki Yamanaka

Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks

Masaki Murakami, Nicolas Dubrana, Yoshihiko Uematsu, Satoru Okamoto, Naoaki Yamanaka

Department of Information and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	2021 Opto-Electronics and Communications Conference, OECC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781943580927
Publication status	Published - 2021
Event	2021 Opto-Electronics and Communications Conference, OECC 2021 - Hong Kong, Hong Kong Duration: 2021 Jul 3 → 2021 Jul 7

Publication series

Name	2021 Opto-Electronics and Communications Conference, OECC 2021

Conference

Conference	2021 Opto-Electronics and Communications Conference, OECC 2021
Country/Territory	Hong Kong
City	Hong Kong
Period	21/7/3 → 21/7/7

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Artificial Intelligence

Cite this

Murakami, M., Dubrana, N., Uematsu, Y., Okamoto, S., & Yamanaka, N. (2021). Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks. In 2021 Opto-Electronics and Communications Conference, OECC 2021 (2021 Opto-Electronics and Communications Conference, OECC 2021). Institute of Electrical and Electronics Engineers Inc..

Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks. / Murakami, Masaki; Dubrana, Nicolas; Uematsu, Yoshihiko et al.
2021 Opto-Electronics and Communications Conference, OECC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 Opto-Electronics and Communications Conference, OECC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Murakami, M, Dubrana, N, Uematsu, Y, Okamoto, S & Yamanaka, N 2021, Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks. in 2021 Opto-Electronics and Communications Conference, OECC 2021. 2021 Opto-Electronics and Communications Conference, OECC 2021, Institute of Electrical and Electronics Engineers Inc., 2021 Opto-Electronics and Communications Conference, OECC 2021, Hong Kong, Hong Kong, 21/7/3.

Murakami M, Dubrana N, Uematsu Y, Okamoto S, Yamanaka N. Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks. In 2021 Opto-Electronics and Communications Conference, OECC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 Opto-Electronics and Communications Conference, OECC 2021).

Murakami, Masaki ; Dubrana, Nicolas ; Uematsu, Yoshihiko et al. / Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks. 2021 Opto-Electronics and Communications Conference, OECC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 Opto-Electronics and Communications Conference, OECC 2021).

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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 Publisher Copyright: {\textcopyright} 2021 The Author(s) ; 2021 Opto-Electronics and Communications Conference, OECC 2021 ; Conference date: 03-07-2021 Through 07-07-2021",

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AU - Okamoto, Satoru

AU - Yamanaka, Naoaki

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PY - 2021

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M3 - Conference contribution

AN - SCOPUS:85139073774

T3 - 2021 Opto-Electronics and Communications Conference, OECC 2021

BT - 2021 Opto-Electronics and Communications Conference, OECC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 3 July 2021 through 7 July 2021

ER -

Kalman Filter-based Heavy Hadoop Job Detection Method for Energy Efficient Hybrid Electro-Optical Intra-Data Center Networks

Abstract

Publication series

Conference

ASJC Scopus subject areas

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