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Evaluation of energy profiles for mobile video prefetching in generalized stochastic access channels
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Mobile Service Laboratory (MS Lab).
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Mobile Service Laboratory (MS Lab). KTH, School of Information and Communication Technology (ICT), Centres, Center for Wireless Systems, Wireless@kth.
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Mobile Service Laboratory (MS Lab). KTH, School of Information and Communication Technology (ICT), Centres, Center for Wireless Systems, Wireless@kth.
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Mobile Service Laboratory (MS Lab). KTH, School of Information and Communication Technology (ICT), Centres, Center for Wireless Systems, Wireless@kth.ORCID iD: 0000-0002-9554-0071
2014 (English)In: Mobile and Ubiquitous Systems: Computing, Networking, and Services: 10th International Conference, MOBIQUITOUS 2013, Tokyo, Japan, December 2-4, 2013, Revised Selected Papers, Springer, 2014, 209-223 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper evaluates the energy cost reduction of Over-The-Top mobile video content prefetching in various network conditions. Energy cost reduction is achieved by reducing the time needed to download content over the radio interface by prefetching data on higher data rates, compared to the standard on demand download. To simulate various network conditions and user behavior, a stochastic access channel model was built and validated using the actual user traces. By changing the model parameters, the energy cost reduction of prefetching in different channel settings was determined, identifying regions in which prefetching is likely to deliver the largest energy gains. The results demonstrate that the largest gains (up to 70%) can be obtained for data rates with strong correlation and low noise variation. Additionally, based on statistical properties of data rates, such as peak-to-mean and average data rate, prefetching strategy can be devised enabling the highest energy cost reduction that can be obtained using the proposed prefetching scheme.

Place, publisher, year, edition, pages
Springer, 2014. 209-223 p.
Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISSN 1867-8211 ; 131
Keyword [en]
Energy profiles, stochastic access channel, mobile video prefetching
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-136739DOI: 10.1007/978-3-319-11569-6_17ISI: 000352148200017Scopus ID: 2-s2.0-84910601630ISBN: 978-331911568-9 (print)OAI: oai:DiVA.org:kth-136739DiVA: diva2:676942
Conference
10th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services; Tokyo, Japan, 2–4 December, 2013
Projects
COSEM - COnvergent and SEmantic-aware Mobile networks and services
Note

QC 20150512

Available from: 2013-12-08 Created: 2013-12-08 Last updated: 2015-11-13Bibliographically approved
In thesis
1. On Optimization of Quality of User Experience and Wireless Network Bandwidth in Video Content Delivery
Open this publication in new window or tab >>On Optimization of Quality of User Experience and Wireless Network Bandwidth in Video Content Delivery
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Mobile video content today generates more than half of the mobile data traffic.The increasing popularity of mobile video on demand services poses great challenges to mobile operators and content providers. Frontmost, how to reduce the mobile video traffic load, while delivering high quality video content to mobile users without perceived quality degradations for the same (or cheaper) price? Battery lifetime represents another key factor of a user’s Quality of Experience(QoE). A lot of device energy is consumed by mobile network signalling and data transmission over new generation mobile communication systems. This thesis focuses on: (1) reducing the size of the video that is delivered to the enduser in the maximum achievable video quality, thus optimizing the wireless network bandwidth and the user-perceived QoE, and (2) reducing the energy consumption of a mobile device that is associated to data transfer over the radio interface, thus increasing the device’s battery lifetime. The main contributions have been given in providing the Over-the-Top video optimization and delivery schemes and recommendations on tuning their parameters in order to minimize the bandwidth and energy consumption of mobile video delivery, while maximizing the predictable user-perceived QoE. By preventing the video to be prefetched on low data rates and tuning the datarate threshold according to statistical properties of available data rates, we show that 20-70% of energy cost can be reduced by opportunistic prefetching, depending on the user’s pattern of available data rates. The data rate values ordered in time that have a large amount of serial correlation and low noise variance, or low average valueand high peak-to-mean ratio, are likely to yield the highest energy gains from content prefetching. Moreover, we show that energy gains are the largest when the threshold data rate is set close to an average data rate, due to the highest availability of data rates around this value, and for longer sleep time between the prefetching periods, which increases the probability of moving away from the areas with low data rates. Next, we focus on QoE-aware mobile video delivery solutions that are more bandwidth efficient without compromising the user-perceived video quality. They deliver a video over a varying data rate channel that is optimized for viewing on a mobile device in the highest perceptual video quality that can be achieved in the given video and network conditions. An optimized video consists of short segments in the minimum resolutions that satisfy the target perceptual video quality and have up to 60% reduced size compared to the video in the corresponding fixed video resolution, without perceptible quality difference. The delivery is performed by on demand download, context-aware prefetching, or in real time using the QoE-aware adaptive video streaming that runs over Dynamic Adaptive video Streaming over HTTP (DASH). By limiting the maximum bitrates of the requested video segments and using the remaining throughput to prefetch optimized video segments in advance of playout, we show that QoE-aware adaptive video streaming maintains a more stable perceptual video quality than DASH despite the fluctuations of the channel bandwidth, while using fewer number of bits, which improves a user-perceived QoE. The results of this thesis can help operators and content providers to reduce their costs and provide more content to their users at the same (or cheaper) price.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xii, 174 p.
Series
TRITA-ICT, 2015:17
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-177011 (URN)978-91-7595-739-5 (ISBN)
Public defence
2015-12-04, Sal/hall B, Electrum , KTH-ICT, Kista, 13:00 (English)
Opponent
Supervisors
Note

QC 20151113

Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2015-11-13Bibliographically approved

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