Presentation 2017-11-17
[Encouragement Talk] Reinforcement Learning based Automated Process Generation for Virtual Network Update
Manabu Nakanoya,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Spreading the network virtualization and softwarization technology using network function virtualization(NFV) and software-defined networking(SDN), provisioning automation software which has control functions for virtualized network functions(VNFs) and SDN controllers is being developed. These software can easily collect various log data at once and change configurations. Therefore, users can utilize it to automate not only simple routine operation, but also for machine learning technology that can learn optimized operation and execute it. Especially, reinforcement learning, which can learn from large number of trials, has been studied to apply various cases because it became easy to execute many trials with software. However, existing automated IT resource control technologies using reinforcement learning are only for the cases where reduction of search space such as allocation of virtual machine, and search efficiency are easy. Hence, it is difficult to learn control tasks which may contain extensive search space such as IP address range. In this paper, I propose (1) a framework which can easily define and execute reinforcement learning with provisioning automation software and (2) a fast learning algorithm that can execute learning including parameters with vast choices where the efficient searching method is not trivial. In Addition, I evaluate its effectiveness through actual update task of virtual network devices executed on the framework (1).
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Reinforcement Learning / Virtual Network / Configuration Update
Paper # ICM2017-32
Date of Issue 2017-11-09 (ICM)

Conference Information
Committee ICM / CQ / NS
Conference Date 2017/11/16(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Toshio Tonouchi(NEC) / Takanori Hayashi(Hiroshima Inst. of Tech.) / Hideki Tode(Osaka Pref. Univ.)
Vice Chair Yuji Nomura(Fujitsu Labs.) / Yoichi Yamashita(NTT-N) / Hideyuki Shimonishi(NEC) / Jun Okamoto(NTT) / Yoshikatsu Okazaki(NTT)
Secretary Yuji Nomura(Fujitsu) / Yoichi Yamashita(KDDI R&D Labs.) / Hideyuki Shimonishi(NTT) / Jun Okamoto(Keio Univ.) / Yoshikatsu Okazaki(Kyushu Inst. of Tech.)
Assistant Haruo Ooishi(NTT) / Kenko Ota(Nippon Inst. of Tech.) / Norihiro Fukumoto(KDDI R&D Labs.) / Ryo Yamamoto(UEC) / Kenichi Kashibuchi(NTT)

Paper Information
Registration To Technical Committee on Information and Communication Management / Technical Committee on Communication Quality / Technical Committee on Network Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Encouragement Talk] Reinforcement Learning based Automated Process Generation for Virtual Network Update
Sub Title (in English)
Keyword(1) Reinforcement Learning
Keyword(2) Virtual Network
Keyword(3) Configuration Update
1st Author's Name Manabu Nakanoya
1st Author's Affiliation NEC Corporation(NEC)
Date 2017-11-17
Paper # ICM2017-32
Volume (vol) vol.117
Number (no) ICM-305
Page pp.pp.63-68(ICM),
#Pages 6
Date of Issue 2017-11-09 (ICM)