Prefetching Schemes and Performance Analysis for TV on Demand Services
(2015) In International Journal on Advances in Telecommunications 8(3&4). p.162-172- Abstract
- TV-on-Demand services have become one of the most
popular Internet applications that continuously attracts high
user interest. With rapidly increasing user demands, the existing
network conditions may not be able to ensure a low start-up delay
of video playback. Prefetching has been broadly investigated to
cope with the start-up latency problem, which is also known as
user perceived latency. In this paper, two datasets from different
IPTV providers are used to analyse the TV program request
patterns. According to the results, we propose a prefetching
scheme at the user end to preload videos before user requests.
For both datasets, our prefetching... (More) - TV-on-Demand services have become one of the most
popular Internet applications that continuously attracts high
user interest. With rapidly increasing user demands, the existing
network conditions may not be able to ensure a low start-up delay
of video playback. Prefetching has been broadly investigated to
cope with the start-up latency problem, which is also known as
user perceived latency. In this paper, two datasets from different
IPTV providers are used to analyse the TV program request
patterns. According to the results, we propose a prefetching
scheme at the user end to preload videos before user requests.
For both datasets, our prefetching scheme significantly improves
the cache hit ratio compared to passive caching and we note that
there is a potential to further improve prefetching performance
by customizing prefetching schemes for different video categories.
We further present a cost model to determine the optimal number
of videos to prefetch. We also discuss if there is enough time for
prefetching. Finally, more factors, which may have an impact on
optimizing prefetching performance, are further discussed, such
as the jump patterns over different time in a day and the the
distribution of each video’s viewing length. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8520362
- author
- Du, Manxing ; Kihl, Maria LU ; Arvidsson, Åke ; Zhang, Huimin ; Lagerstedt, Christina and Gavler, Anders
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- International Journal on Advances in Telecommunications
- volume
- 8
- issue
- 3&4
- pages
- 162 - 172
- publisher
- IARIA
- ISSN
- 1942-2601
- project
- EIT_NOTTS Next generation over-the-top multimedia services
- LCCC
- language
- English
- LU publication?
- yes
- id
- ca79ccd2-3d60-49fb-8e42-8a7250012788 (old id 8520362)
- date added to LUP
- 2016-04-01 13:06:48
- date last changed
- 2018-11-21 20:12:21
@article{ca79ccd2-3d60-49fb-8e42-8a7250012788,
abstract = {{TV-on-Demand services have become one of the most<br/><br>
popular Internet applications that continuously attracts high<br/><br>
user interest. With rapidly increasing user demands, the existing<br/><br>
network conditions may not be able to ensure a low start-up delay<br/><br>
of video playback. Prefetching has been broadly investigated to<br/><br>
cope with the start-up latency problem, which is also known as<br/><br>
user perceived latency. In this paper, two datasets from different<br/><br>
IPTV providers are used to analyse the TV program request<br/><br>
patterns. According to the results, we propose a prefetching<br/><br>
scheme at the user end to preload videos before user requests.<br/><br>
For both datasets, our prefetching scheme significantly improves<br/><br>
the cache hit ratio compared to passive caching and we note that<br/><br>
there is a potential to further improve prefetching performance<br/><br>
by customizing prefetching schemes for different video categories.<br/><br>
We further present a cost model to determine the optimal number<br/><br>
of videos to prefetch. We also discuss if there is enough time for<br/><br>
prefetching. Finally, more factors, which may have an impact on<br/><br>
optimizing prefetching performance, are further discussed, such<br/><br>
as the jump patterns over different time in a day and the the<br/><br>
distribution of each video’s viewing length.}},
author = {{Du, Manxing and Kihl, Maria and Arvidsson, Åke and Zhang, Huimin and Lagerstedt, Christina and Gavler, Anders}},
issn = {{1942-2601}},
language = {{eng}},
number = {{3&4}},
pages = {{162--172}},
publisher = {{IARIA}},
series = {{International Journal on Advances in Telecommunications}},
title = {{Prefetching Schemes and Performance Analysis for TV on Demand Services}},
url = {{https://lup.lub.lu.se/search/files/3165490/8520367.pdf}},
volume = {{8}},
year = {{2015}},
}