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Paper Abstract and Keywords
Presentation 2023-09-08 14:20
Power Consumption Optimization Method for Distributed Video Analysis System by Artificial Gene Regulatory Networks
Seishiro Inoue, Masaaki Yamauchi, Daichi Kominami, Hideyuki Shimonishi, Masayuki Murata (Osaka Univ.) NS2023-64
Abstract (in Japanese) (See Japanese page) 
(in English) A digital twin highly integrates real and virtual worlds.
To construct it, we must accurately perceive the current state of the real world.
Thus, we need to analyze a lot of video data obtained from the real world in real-time.
However, a lot of network traffic of the data increases power consumption.
An approach for this problem is a distributed video analysis system using edge servers. The system requires dynamic control considering network congestion, application requirements, etc.
Our research group formulated the dynamic control as an optimization problem and solved it using genetic algorithms to reduce power consumption.
In this paper, we applied gene regulatory networks to the genetic algorithms.
The phenotypic bias of the gene regulatory networks allows for quick recall of specific phenotypes, i.e., optimal solution.
We demonstrated the gene regulatory networks select the optimal solution experienced in the past quickly; our method could reduce the power consumption continuously and stably.
Keyword (in Japanese) (See Japanese page) 
(in English) Digital twin / adaptive evolution / optimization problem / genetic algorithm / gene regulatory network / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 177, NS2023-64, pp. 71-76, Sept. 2023.
Paper # NS2023-64 
Date of Issue 2023-08-31 (NS) 
ISSN Online edition: ISSN 2432-6380
Copyright
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NS2023-64

Conference Information
Committee NS IN CS NV  
Conference Date 2023-09-07 - 2023-09-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Session management (SIP/IMS), Interoperability/Standardization, NGN/NwGN/Future networks, Cloud/Data center networks, SDN (OpenFlow, etc.)/NFV, IPv6, Machine learning, etc. 
Paper Information
Registration To NS 
Conference Code 2023-09-NS-IN-CS-NV 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Power Consumption Optimization Method for Distributed Video Analysis System by Artificial Gene Regulatory Networks 
Sub Title (in English)  
Keyword(1) Digital twin  
Keyword(2) adaptive evolution  
Keyword(3) optimization problem  
Keyword(4) genetic algorithm  
Keyword(5) gene regulatory network  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Seishiro Inoue  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Masaaki Yamauchi  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Daichi Kominami  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Hideyuki Shimonishi  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name Masayuki Murata  
5th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2023-09-08 14:20:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2023-64 
Volume (vol) vol.123 
Number (no) no.177 
Page pp.71-76 
#Pages 6 
Date of Issue 2023-08-31 (NS) 


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