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Prefetching Schemes and Performance Analysis for TV on Demand Services

Du, Manxing; Kihl, Maria LU ; Arvidsson, Åke; Zhang, Huimin; Lagerstedt, Christina and Gavler, Anders (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:
author
organization
publishing date
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
2016-01-18 11:11:34
date last changed
2016-04-15 21:29:19
@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},
  volume       = {8},
  year         = {2015},
}