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Evaluation of context distribution methods via Bluetooth and WLAN: Insights gained while examining Battery Power Consumption
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
2008 (English)In: MobiQuitous 2008 - 5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2008Conference paper, Published paper (Refereed)
Abstract [en]

In a traditional context-aware system, most context information is local to a device. However, we may need access to context information from outside the device. Increasingly mobile electronic devices are equipped with Bluetooth and/or WLAN network interfaces. Both of these technologies enable ad hoc discovery & networking. In this paper we evaluate the use of these technologies for context distribution within a local area (i.e., limited to a single hop). Using Bluetooth, we begin by discovering devices using Bluetooth's discovery protocol, collect their context information, create an XML file containing this information, and distribute this file to all discovered devices, such that every device now has the same context information. Next we perform the same discovery, collect, and distribute functions, but using WLAN. In each case we have performed the cycle of operations starting with a fully charged battery and continuing until the device was not able to utilize the selected wireless interface any longer. Finally we compare both approaches to context distribution in terms of battery power consumption. We observe that Bluetooth consumes 2-6 times more energy for transmission of a 1MB file to two devices than to discover these two devices. Furthermore, the transfer of this file is two times slower than WLAN, and we must unicast this file to each device. Multicasting via WLAN proved to be less energy consuming than the Bluetooth transmission, if data is to be sent to more than three users. In addition, the energy to discover 2 devices along with their services using Bluetooth consumed 52 times more energy than to receive the same amount of data via a WLAN multicast. Thus, this paper shows that it is more energy efficient to distribute context knowledge to other devices, than having each device learn this information itself. Finally, we give equations for calculating the battery power consumption of transmitting data using any protocol that runs over Bluetooth or over WLAN.

Place, publisher, year, edition, pages
2008.
Keyword [en]
Battery power evaluation, Bluetooth, Context distribution, WLAN, Electric batteries, Energy efficiency, Multicasting, Semantics, Ubiquitous computing, Battery power, Battery power consumption, Context information, Context-aware systems, Mobile electronics, Wireless interfaces, Electron devices
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-167716DOI: 10.4108/ICST.MOBIQUITOUS2008.3613Scopus ID: 2-s2.0-84923164071ISBN: 9789639799219 (print)OAI: oai:DiVA.org:kth-167716DiVA: diva2:815859
Conference
5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2008, Dublin, Ireland, 21-25 July 2008
Note

QC 20150602

Available from: 2015-06-02 Created: 2015-05-22 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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