Prefetching Method for Low-Latency Web AR in the WMN Edge Server
Recently, low-latency services for large-capacity data have been studied given the development of edge servers and wireless mesh networks. The 3D data provided for augmented reality (AR) services have a larger capacity than general 2D data. In the conventional WebAR method, a variety of data such as...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/1/133 |
| _version_ | 1797626355361251328 |
|---|---|
| author | Seyun Choi Sukjun Hong Hoijun Kim Seunghyun Lee Soonchul Kwon |
| author_facet | Seyun Choi Sukjun Hong Hoijun Kim Seunghyun Lee Soonchul Kwon |
| author_sort | Seyun Choi |
| collection | DOAJ |
| description | Recently, low-latency services for large-capacity data have been studied given the development of edge servers and wireless mesh networks. The 3D data provided for augmented reality (AR) services have a larger capacity than general 2D data. In the conventional WebAR method, a variety of data such as HTML, JavaScript, and service data are downloaded when they are first connected. The method employed to fetch all AR data when the client connects for the first time causes initial latency. In this study, we proposed a prefetching method for low-latency AR services. Markov model-based prediction via the partial matching (PPM) algorithm was applied for the proposed method. Prefetched AR data were predicted during AR services. An experiment was conducted at the Nowon Career Center for Youth and Future in Seoul, Republic of Korea from 1 June 2022 to 31 August 2022, and a total of 350 access data points were collected over three months; the prefetching method reduced the average total latency of the client by 81.5% compared to the conventional method. |
| first_indexed | 2024-03-11T10:09:14Z |
| format | Article |
| id | doaj.art-bb1370a9836a4a3680b9ea1d09d4f927 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:09:14Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-bb1370a9836a4a3680b9ea1d09d4f9272023-11-16T14:51:08ZengMDPI AGApplied Sciences2076-34172022-12-0113113310.3390/app13010133Prefetching Method for Low-Latency Web AR in the WMN Edge ServerSeyun Choi0Sukjun Hong1Hoijun Kim2Seunghyun Lee3Soonchul Kwon4Department of Smart System, Kwangwoon University, Seoul 01897, Republic of KoreaDepartment of Smart System, Kwangwoon University, Seoul 01897, Republic of KoreaDepartment of Plasma Bio Display, Kwangwoon University, Seoul 01897, Republic of KoreaDepartment of Ingenium College Liberal Arts, Kwangwoon University, Seoul 01897, Republic of KoreaGraduate School of Smart Convergence, Kwangwoon University, Seoul 01897, Republic of KoreaRecently, low-latency services for large-capacity data have been studied given the development of edge servers and wireless mesh networks. The 3D data provided for augmented reality (AR) services have a larger capacity than general 2D data. In the conventional WebAR method, a variety of data such as HTML, JavaScript, and service data are downloaded when they are first connected. The method employed to fetch all AR data when the client connects for the first time causes initial latency. In this study, we proposed a prefetching method for low-latency AR services. Markov model-based prediction via the partial matching (PPM) algorithm was applied for the proposed method. Prefetched AR data were predicted during AR services. An experiment was conducted at the Nowon Career Center for Youth and Future in Seoul, Republic of Korea from 1 June 2022 to 31 August 2022, and a total of 350 access data points were collected over three months; the prefetching method reduced the average total latency of the client by 81.5% compared to the conventional method.https://www.mdpi.com/2076-3417/13/1/133wireless mesh networkedge serveraugmented realityprefetching |
| spellingShingle | Seyun Choi Sukjun Hong Hoijun Kim Seunghyun Lee Soonchul Kwon Prefetching Method for Low-Latency Web AR in the WMN Edge Server Applied Sciences wireless mesh network edge server augmented reality prefetching |
| title | Prefetching Method for Low-Latency Web AR in the WMN Edge Server |
| title_full | Prefetching Method for Low-Latency Web AR in the WMN Edge Server |
| title_fullStr | Prefetching Method for Low-Latency Web AR in the WMN Edge Server |
| title_full_unstemmed | Prefetching Method for Low-Latency Web AR in the WMN Edge Server |
| title_short | Prefetching Method for Low-Latency Web AR in the WMN Edge Server |
| title_sort | prefetching method for low latency web ar in the wmn edge server |
| topic | wireless mesh network edge server augmented reality prefetching |
| url | https://www.mdpi.com/2076-3417/13/1/133 |
| work_keys_str_mv | AT seyunchoi prefetchingmethodforlowlatencywebarinthewmnedgeserver AT sukjunhong prefetchingmethodforlowlatencywebarinthewmnedgeserver AT hoijunkim prefetchingmethodforlowlatencywebarinthewmnedgeserver AT seunghyunlee prefetchingmethodforlowlatencywebarinthewmnedgeserver AT soonchulkwon prefetchingmethodforlowlatencywebarinthewmnedgeserver |