| Issue |
SHS Web Conf.
Volume 77, 2020
The 2nd ACM Chapter International Conference on Educational Technology, Language and Technical Communication (ETLTC2020)
|
|
|---|---|---|
| Article Number | 04007 | |
| Number of page(s) | 4 | |
| Section | Topics in Computer Science | |
| DOI | https://doi.org/10.1051/shsconf/20207704007 | |
| Published online | 08 May 2020 | |
Assessment of TCP Multi-Pathization Method on IoT Devices by SDN based on WebQoE
Nagoya Institute of Technology, Graduate School of Engineering, Computer Science and Engineering, Gokiso, Nagoya city, Aichi prefecture, Japan
* e-mail: yuki@en.nitech.ac.jp
** e-mail: yoshi@en.nitech.ac.jp
This paper assesses QoE for a Web service (WebQoE) for the TCP multi-pathization method by SDN by experiments with subjects. The multi-pathization method is one of the QoS controls for IoT networks; it can multi-pathize a TCP connection without any changes of terminals or protocols. The previous work of the authors has evaluated QoS of Web services but has not assessed QoE. This paper assesses QoE of an online map service for the multi-pathization method by experiments with subjects. In the experiment, the authors treat various environments which differs in the amount of load traffic. The obtained results show that WebQoE for the multi-pathization method is always higher than that without the method. Consequently, the paper confirms that the multi-pathization is effective from point of users’ view.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.