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Context retrieval and distribution in a mobile distributed environment
2007 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Context-aware services are gaining momentum in mobile computing. To enable rapid development of context-aware services,context information has to be retrieved from the environment, modeled,processed, and distributed to these services. MIDAS is a European research project concerning 3G and beyond, which aims to dene and implement a platform to simplify and speed up the task of developing and deploying mobile applications and services. MIDAS context engine provides mechanisms to retrieve, model, synthesize, and distribute context information in a distributed, mobile environment. This paper presents a way to retrieve and distribute context information using context queries and triggers. A novel approach to perform context synthesis will be presented using operators.

Place, publisher, year, edition, pages
2007.
Keyword [en]
Distributed context engine, context query, context trigger, context synthesis, context retrieval and distribution
National Category
Communication Systems
Research subject
Information and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-176929OAI: oai:DiVA.org:kth-176929DiVA: diva2:869097
Conference
Third Workshop on Context Awareness for Proactive Systems (CAPS 2007)
Note

QC 20151113

Available from: 2015-11-12 Created: 2015-11-12 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

Open Access in DiVA

fulltext(266 kB)66 downloads
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Citation style
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Output format
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