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Paper Abstract and Keywords
Presentation 2021-09-09 14:30
[Invited Lecture] A Proposal and Implementation of Adaptive Distributed Compressed Sensing with Cooperative Optimization among Edge Devices
Masatoshi Sekine, Kengo Okano, Satoshi Ikada (OKI) NS2021-64
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, monitoring systems that utilize IoT have become important in monitoring social infrastructure and factory equipment. It is important to reduce the amount of transmission on the edge side while suppressing the deterioration of quality of sensor data from multiple locations. We propose a highly efficient multi-agent method for compressing and reconstructing with a smaller amount of transmitted data than our single-agent method. It coordinates transmitting terminals and relay terminals and learns the optimal compression ratio based on multi-agent deep reinforcement learning. In this paper, we introduce the method and evaluate the performance in a distributed environment using sensor nodes composed of Raspberry Pi Zero WH equipped with MEMS accelerometer. As a result, we found that the amount of data transmission can be reduced compared to the single-agent method while suppressing the reconstruction error.
Keyword (in Japanese) (See Japanese page) 
(in English) distributed compressed sensing / multi-agent deep reinforcement learning / sensor data / edge device / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 170, NS2021-64, pp. 42-47, Sept. 2021.
Paper # NS2021-64 
Date of Issue 2021-09-02 (NS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 NS2021-64

Conference Information
Committee IN NS CS NV  
Conference Date 2021-09-09 - 2021-09-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
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 2021-09-IN-NS-CS-NV 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Proposal and Implementation of Adaptive Distributed Compressed Sensing with Cooperative Optimization among Edge Devices 
Sub Title (in English)  
Keyword(1) distributed compressed sensing  
Keyword(2) multi-agent deep reinforcement learning  
Keyword(3) sensor data  
Keyword(4) edge device  
1st Author's Name Masatoshi Sekine  
1st Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
2nd Author's Name Kengo Okano  
2nd Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
3rd Author's Name Satoshi Ikada  
3rd Author's Affiliation Oki Electric Industry Co., Ltd. (OKI)
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Date Time 2021-09-09 14:30:00 
Presentation Time 25 
Registration for NS 
Paper # IEICE-NS2021-64 
Volume (vol) IEICE-121 
Number (no) no.170 
Page pp.42-47 
#Pages IEICE-6 
Date of Issue IEICE-NS-2021-09-02 

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