Paper Abstract and Keywords |
Presentation |
2019-05-23 16:20
Characteristic Analysis of Time-series P2PTV Traffic Using Machine Learning Rina Ooka, Koji Hayashi, Takumi Miyoshi, Taku Yamazaki (Shibaura Inst. of Tech.) ICM2019-2 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
P2P-based video streaming service (P2PTV) in which user terminals (peers) directly communicate with each other has attracted attention due to the increase of users who enjoy video distribution services.
P2PTV can distribute the data delivery load concentrated to the video servers since peers share and transfer the video data among them.
To maintain the network properly, it is necessary to understand the characteristics of P2PTV traffic in advance. Since each video content has a different popularity and data size, the number of peers that share the same video data and the throughput may greatly fluctuate.
In our previous studies, we have obtained P2PTV traffic in watching each video content for a long time and analyzed the characteristics by classifying the obtained traffic data.
However, users would participate in or leave from P2PTV services dynamically, and then the traffic characteristics may change from moment to moment: The classification and analysis of traffic characteristics on a per content basis must be therefore insufficient.
In this paper, we propose a time-series P2PTV traffic classification method. The proposed method divides P2PTV traffic into short-time data pieces to create time series data, and classifies these data by machine learning.
We also analyze traffic characteristics from the classification results of 80 P2PTV traffic data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
P2P / P2PTV / Machine learning / Traffic analysis / Clustering / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 52, ICM2019-2, pp. 31-36, May 2019. |
Paper # |
ICM2019-2 |
Date of Issue |
2019-05-16 (ICM) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and 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 |
ICM2019-2 |
Conference Information |
Committee |
ICM IPSJ-CSEC IPSJ-IOT |
Conference Date |
2019-05-23 - 2019-05-24 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
|
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
|
Paper Information |
Registration To |
ICM |
Conference Code |
2019-05-ICM-CSEC-IOT |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Characteristic Analysis of Time-series P2PTV Traffic Using Machine Learning |
Sub Title (in English) |
|
Keyword(1) |
P2P |
Keyword(2) |
P2PTV |
Keyword(3) |
Machine learning |
Keyword(4) |
Traffic analysis |
Keyword(5) |
Clustering |
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Rina Ooka |
1st Author's Affiliation |
Shibaura Institute of Technology (Shibaura Inst. of Tech.) |
2nd Author's Name |
Koji Hayashi |
2nd Author's Affiliation |
Shibaura Institute of Technology (Shibaura Inst. of Tech.) |
3rd Author's Name |
Takumi Miyoshi |
3rd Author's Affiliation |
Shibaura Institute of Technology (Shibaura Inst. of Tech.) |
4th Author's Name |
Taku Yamazaki |
4th Author's Affiliation |
Shibaura Institute of Technology (Shibaura Inst. of Tech.) |
5th Author's Name |
|
5th Author's Affiliation |
() |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-1 |
Date Time |
2019-05-23 16:20:00 |
Presentation Time |
25 minutes |
Registration for |
ICM |
Paper # |
ICM2019-2 |
Volume (vol) |
vol.119 |
Number (no) |
no.52 |
Page |
pp.31-36 |
#Pages |
6 |
Date of Issue |
2019-05-16 (ICM) |
|