Prefetching Schemes and Performance Analysis for TV on Demand Services
Author
Summary, in English
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.
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.
Department/s
Publishing year
2015
Language
English
Pages
162-172
Publication/Series
International Journal on Advances in Telecommunications
Volume
8
Issue
3&4
Full text
Document type
Journal article
Publisher
IARIA
Topic
- Electrical Engineering, Electronic Engineering, Information Engineering
Status
Published
Project
- EIT_NOTTS Next generation over-the-top multimedia services
- LCCC
Research group
- Broadband Communication
ISBN/ISSN/Other
- ISSN: 1942-2601