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Paper Abstract and Keywords
Presentation 2020-09-03 11:45
Study on the Effectivity of Rendezvous Search Using Random Walk in Large-Scale Unknown Networks
Fumiya Toyoda, Yusuke Sakumoto, Hiroyuki Ohsaki (Kwansei Univ.) CQ2020-37
Abstract (in Japanese) (See Japanese page) 
(in English) Many studies proposed a rendezvous search method that multiple searchers starting from different nodes on a network try to meet at the same node. Among the methods, rendezvous search methods on unknown networks, where each node can only obtain the information of its adjacent nodes, is expected for utilizing various networks, such as mobile ad-hoc network and social network. We has proposed a rendezvous search method (a random walk search method) using random walks in order to reduce the load of a flooding search method, which can perform the fastest rendezvous search on unknown networks. Although the random walk search method will be used in large-scale networks, we do not clarify its effectiveness. In this paper, we evaluate the effectiveness of the random walk search method in large-scale networks, by the comparison with the flooding search method. According to the results, we show the high effectiveness of the random walk search in large-scale scale-free networks. Especially, in the networks with 10, 000 nodes, the random walk search can finish as fast as the flooding search with while its load is 0.2% lower than that of the flooding search.
Keyword (in Japanese) (See Japanese page) 
(in English) Rendezvous Search / Flooding / Random Walk / Large-Scale Network / Scale-Free Property / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 155, CQ2020-37, pp. 15-20, Sept. 2020.
Paper # CQ2020-37 
Date of Issue 2020-08-27 (CQ) 
ISSN Print edition: ISSN 0913-5685  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 CQ2020-37

Conference Information
Committee CQ  
Conference Date 2020-09-03 - 2020-09-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka University Nakanoshima Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Machine Learning in Wireless Communication, AI, 6G/Beyond 5G, LPWA, Drone Network, Communications in Extreme Environments, Wireless Networks, QoS and QoE in Wireless Communication, Wireless Resource Allocation, Wireless Transmission Quality, Cross layer Technology, Ad-hoc Network, IoT/M2M, Wireless, etc. 
Paper Information
Registration To CQ 
Conference Code 2020-09-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on the Effectivity of Rendezvous Search Using Random Walk in Large-Scale Unknown Networks 
Sub Title (in English)  
Keyword(1) Rendezvous Search  
Keyword(2) Flooding  
Keyword(3) Random Walk  
Keyword(4) Large-Scale Network  
Keyword(5) Scale-Free Property  
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1st Author's Name Fumiya Toyoda  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Univ.)
2nd Author's Name Yusuke Sakumoto  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Univ.)
3rd Author's Name Hiroyuki Ohsaki  
3rd Author's Affiliation Kwansei Gakuin University (Kwansei Univ.)
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Speaker
Date Time 2020-09-03 11:45:00 
Presentation Time 25 
Registration for CQ 
Paper # IEICE-CQ2020-37 
Volume (vol) IEICE-120 
Number (no) no.155 
Page pp.15-20 
#Pages IEICE-6 
Date of Issue IEICE-CQ-2020-08-27 


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