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SIP-based context distribution: Does aggregation pay off?
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture (Closed 20120101), Communication Systems, CoS (closed 2012-01-01).
2010 (English)In: Computer communication review, ISSN 0146-4833, E-ISSN 1046-4833, Vol. 40, no 5, 35-46 p.Article in journal (Refereed) Published
Abstract [en]

Context-aware applications need quickly access to current context information, in order to adapt their behavior before this context changes. To achieve this, the context distribution mechanism has to timely discover context sources that can provide a particular context type, then acquire and distribute context information from these sources to the applications that requested this type of information. This paper reviews the state-of-the-art context distribution mechanisms according to identified requirements, then introduces a resource list-based subscription/notification mechanism for context sharing. This SIP-based mechanism enables subscriptions to a resource list containing URIs of multiple context sources that can provide the same context type and delivery of aggregated notifications containing context updates from each of these sources. Aggregation of context is thought to be important as it reduces the network traffic between entities involved in context distribution. However, it introduces an additional delay due to waiting for context updates and their aggregation. To investigate if this aggregation actually pays off, we measured and compared the time needed by an application to receive context updates after subscribing to a particular resource list (using RLS) versus after subscribing to each of the individual context sources (using SIMPLE) for different numbers of context sources. Our results show that RLS aggregation outperforms the SIMPLE presence mechanism with 3 or more context sources, regardless of their context updates size. Database performance was identified as a major bottleneck during aggregation, hence we used in-memory tables & prepared statements, leading to up to 57% database time improvement, resulting in a reduction of the aggregation time by up to 34%. With this reduction and an increase in context size, we pushed the aggregation payoff threshold closer to 2 context sources.

Place, publisher, year, edition, pages
2010. Vol. 40, no 5, 35-46 p.
Keyword [en]
Aggregation, Context distribution, RLS, SIMPLE, XCAP
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-148940DOI: 10.1145/1880153.1880159ISI: 000284877800005ScopusID: 2-s2.0-84873688435OAI: diva2:738082

QC 20140815

Available from: 2014-08-15 Created: 2014-08-14 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.
, TRITA-ICT, 2015:17
National Category
Communication Systems
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)

QC 20151113

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

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Devlic, Alisa
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