Presentation 2017-01-19
A Reinforcement Learning-based Data Storage Scheme for VANETs
Celimuge Wu, Tsutomu Yoshinaga, Yusheng Ji,
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Abstract(in English) Vehicular ad hoc networks (VANETs) have been attracting interest for their potential roles in intelligent transport systems (ITS). In order to enable distributed ITS, there is a need to maintain some information in the vehicular networks without the support of any infrastructure such as road side units. In this paper, we propose a protocol which can store the data in VANETs by transferring data to a new carrier (vehicle) before the current data carrier is moving out of a specified region. For the next data carrier node selection, the protocol employs fuzzy logic to evaluate instant reward by taking into account multiple metrics specifically throughput, vehicle velocity, and bandwidth efficiency. In addition, a reinforcement learning-based algorithm is used to consider the future reward of a decision. We use computer simulations to evaluate the proposed protocol.
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Paper # CQ2016-92
Date of Issue 2017-01-12 (CQ)

Conference Information
Committee CQ
Conference Date 2017/1/19(2days)
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Place (in English) Osaka University Nakanoshima Center
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Chair Kyoko Yamori(Asahi Univ.)
Vice Chair Takanori Hayashi(NTT) / Hideyuki Shimonishi(NEC)
Secretary Takanori Hayashi(Osaka Univ.) / Hideyuki Shimonishi(Keio Univ.)
Assistant Hirantha Abeysekera(NTT) / Norihiro Fukumoto(KDDI R&D Labs.)

Paper Information
Registration To Technical Committee on Communication Quality
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Reinforcement Learning-based Data Storage Scheme for VANETs
Sub Title (in English)
Keyword(1)
Keyword(2)
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1st Author's Name Celimuge Wu
1st Author's Affiliation The University of Electro-Communications(UEC)
2nd Author's Name Tsutomu Yoshinaga
2nd Author's Affiliation The University of Electro-Communications(UEC)
3rd Author's Name Yusheng Ji
3rd Author's Affiliation National Institute of Informatics(NII)
Date 2017-01-19
Paper # CQ2016-92
Volume (vol) vol.116
Number (no) CQ-403
Page pp.pp.13-18(CQ),
#Pages 6
Date of Issue 2017-01-12 (CQ)