8 research outputs found
Flow Level QoE of Video Streaming in Wireless Networks
The Quality of Experience (QoE) of streaming service is often degraded by
frequent playback interruptions. To mitigate the interruptions, the media
player prefetches streaming contents before starting playback, at a cost of
delay. We study the QoE of streaming from the perspective of flow dynamics.
First, a framework is developed for QoE when streaming users join the network
randomly and leave after downloading completion. We compute the distribution of
prefetching delay using partial differential equations (PDEs), and the
probability generating function of playout buffer starvations using ordinary
differential equations (ODEs) for CBR streaming. Second, we extend our
framework to characterize the throughput variation caused by opportunistic
scheduling at the base station, and the playback variation of VBR streaming.
Our study reveals that the flow dynamics is the fundamental reason of playback
starvation. The QoE of streaming service is dominated by the first moments such
as the average throughput of opportunistic scheduling and the mean playback
rate. While the variances of throughput and playback rate have very limited
impact on starvation behavior.Comment: 14 page
Outage Performance of Two-Hop OFDM Systems with Spatially Random Decode-and-Forward Relays
In this paper, we analyze the outage performance of different multicarrier
relay selection schemes for two-hop orthogonal frequency-division multiplexing
(OFDM) systems in a Poisson field of relays. In particular, special emphasis is
placed on decode-and-forward (DF) relay systems, equipped with bulk and
per-subcarrier selection schemes, respectively. The exact expressions for
outage probability are derived in integrals for general cases. In addition,
asymptotic expressions for outage probability in the high signal-to-noise ratio
(SNR) region in the finite circle relay distribution region are determined in
closed forms for both relay selection schemes. Also, the outage probabilities
for free space in the infinite relay distribution region are derived in closed
forms. Meanwhile, a series of important properties related to cooperative
systems in random networks are investigated, including diversity, outage
probability ratio of two selection schemes and optimization of the number of
subcarriers in terms of system throughput. All analysis is numerically verified
by simulations. Finally, a framework for analyzing the outage performance of
OFDM systems with spatially random relays is constructed, which can be easily
modified to analyze other similar cases with different forwarding protocols,
location distributions and/or channel conditions
User Quality of Experience (QoE) Satisfaction for Video Content Selection (VCS) Framework in Smartphone Devices
يعد جدول الفديو الاكثر انتشارا اليوم. اضافة الى ذلك، وبسبب انتشار الوباء عالميا، كثير من الناس التزموا المنزل واعتمدوا على الخدمات الجدولية للاخبار والتعليم والتسلية. على اية حال، مستعمل تجربة (QoE (غير مقتنع باختيار محتوى الفديو بينما يتدفق في الاجهزة الذكية. ينزعج المستعملون بمسح نوعية الفيديو الغير متوقعة التي تحدث في اجهزتهم الذكية. في هذا البحث، نقترح مخطط لاختيار الفديو الهيكلي الذي يهدف الى زيادة قناعة مستعمل (QoE ). تم استعمال نظام الحلول الحسابية لاختيار محتوى الفديو لانشاء خريطة لاختيار الفديوالتي ترضي مستعمل نوعية الجدول الاكثراعتبارا. تصنف اختيار محتوى الفديو الى مجاميع صفات الفديو. سينخفض مستوى جدول ( VCS) بالتدريج ليعتبر اقل اختيار الفديو الذي لا يقبلها المستعمل اعتمادا على نوعية الفديو. لتقييم مستوى القناعة ، استعملنا درجة الرأي الوضيع ( MOS) لقياس تكيف قبول المستعمل اتجاه نوعية جدول الفديو. أظهرت النتائج الاخيرة بأن نظام الحلول الحسابية المقترح توضح بأن المستعمل يقتنع باختيار الفديو بواسطة تغيير صفات الفديو. Video streaming is widely available nowadays. Moreover, since the pandemic hit all across the globe, many people stayed home and used streaming services for news, education, and entertainment. However, when streaming in session, user Quality of Experience (QoE) is unsatisfied with the video content selection while streaming on smartphone devices. Users are often irritated by unpredictable video quality format displays on their smartphone devices. In this paper, we proposed a framework video selection scheme that targets to increase QoE user satisfaction. We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. Video Content Selection (VCS) are classified into video attributes groups. The level of VCS streaming will gradually decrease to consider the least video selection that users will not accept depending on video quality. To evaluate the satisfaction level, we used the Mean Opinion Score (MOS) to measure the adaptability of user acceptance towards video streaming quality. The final results show that the proposed algorithm shows that the user satisfies the video selection, by altering the video attributes
A quality of experience approach in smartphone video selection framework for energy efficiency
Online video streaming is getting more common in the smartphone device nowadays.
Since the Corona Virus (COVID-19) pandemic hit all human across the globe in 2020,
the usage of online streaming among smartphone user are getting more vital.
Nevertheless, video streaming can cause the smartphone energy to drain quickly
without user to realize it. Also, saving energy alone is not the most significant issues
especially if with the lack of attention on the user Quality of Experience (QoE). A
smartphones energy management is crucial to overcome both of these issues. Thus, a
QoE Mobile Video Selection (QMVS) framework is proposed. The QMVS
framework will govern the tradeoff between energy efficiency and user QoE in the
smartphone device. In QMVS, video streaming will be using Dynamic Video Attribute
Pre-Scheduling (DVAP) algorithm to determine the energy efficiency in smartphone
devices. This process manages the video attribute such as brightness, resolution, and
frame rate by turning to Video Content Selection (VCS). DVAP is handling a set of
rule in the Rule Post-Pruning (RPP) method to remove an unused node in list tree of
VCS. Next, QoE subjective method is used to obtain the Mean Opinion Score (MOS)
of users from a survey experiment on QoE. After both experiment results (MOS and
energy) are established, the linear regression technique is used to find the relationship
between energy consumption and user QoE (MOS). The last process is to analyze the
relationship of VCS results by comparing the DVAP to other recent video streaming
applications available. Summary of experimental results demonstrate the significant
reduction of 10% to 20% energy consumption along with considerable acceptance of
user QoE. The VCS outcomes are essential to help users and developer deciding which
suitable video streaming format that can satisfy energy consumption and user QoE
Queueing-Theoretic End-to-End Latency Modeling of Future Wireless Networks
The fifth generation (5G) of mobile communication networks is envisioned to enable a variety of novel applications. These applications demand requirements from the network, which are diverse and challenging. Consequently, the mobile network has to be not only capable to meet the demands of one of these applications, but also be flexible enough that it can be tailored to different needs of various services. Among these new applications, there are use cases that require low latency as well as an ultra-high reliability, e.g., to ensure unobstructed production in factory automation or road safety for (autonomous) transportation. In these domains, the requirements are crucial, since violating them may lead to financial or even human damage. Hence, an ultra-low probability of failure is necessary.
Based on this, two major questions arise that are the motivation for this thesis. First, how can ultra-low failure probabilities be evaluated, since experiments or simulations would require a tremendous number of runs and, thus, turn out to be infeasible. Second, given a network that can be configured differently for different applications through the concept of network slicing, which performance can be expected by different parameters and what is their optimal choice, particularly in the presence of other applications.
In this thesis, both questions shall be answered by appropriate mathematical modeling of the radio interface and the radio access network. Thereby the aim is to find the distribution of the (end-to-end) latency, allowing to extract stochastic measures such as the mean, the variance, but also ultra-high percentiles at the distribution tail. The percentile analysis eventually leads to the desired evaluation of worst-case scenarios at ultra-low probabilities. Therefore, the mathematical tool of queuing theory is utilized to study video streaming performance and one or multiple (low-latency) applications. One of the key contributions is the development of a numeric algorithm to obtain the latency of general queuing systems for homogeneous as well as for prioritized heterogeneous traffic. This provides the foundation for analyzing and improving end-to-end latency for
applications with known traffic distributions in arbitrary network topologies and consisting of one or multiple network slices.Es wird erwartet, dass die fünfte Mobilfunkgeneration (5G) eine Reihe neuartiger Anwendungen ermöglichen wird. Allerdings stellen diese Anwendungen sowohl sehr unterschiedliche als auch überaus herausfordernde Anforderungen an das Netzwerk. Folglich muss das mobile Netz nicht nur die Voraussetzungen einer einzelnen Anwendungen erfüllen, sondern auch flexibel genug sein, um an die Vorgaben unterschiedlicher Dienste angepasst werden zu können. Ein Teil der neuen Anwendungen erfordert hochzuverlässige Kommunikation mit niedriger Latenz, um beispielsweise unterbrechungsfreie Produktion in der Fabrikautomatisierung oder Sicherheit im (autonomen) Straßenverkehr zu gewährleisten. In diesen Bereichen ist die Erfüllung der gestellten Anforderungen besonders kritisch, da eine Verletzung finanzielle oder sogar personelle Schäden nach sich ziehen könnte. Eine extrem niedrige Ausfallwahrscheinlichkeit ist daher von größter Wichtigkeit.
Daraus ergeben sich zwei wesentliche Fragestellungen, welche diese Arbeit motivieren. Erstens, wie können extrem niedrige Ausfallwahrscheinlichkeiten evaluiert werden. Ihr Nachweis durch Experimente oder Simulationen würde eine extrem große Anzahl an Durchläufen benötigen und sich daher als nicht realisierbar herausstellen. Zweitens, welche Performanz ist für ein gegebenes Netzwerk durch unterschiedliche Konfigurationen zu erwarten und wie kann die optimale Konfiguration gewählt werden. Diese Frage ist insbesondere dann interessant, wenn mehrere Anwendungen gleichzeitig bedient werden und durch sogenanntes Slicing für jeden Dienst unterschiedliche Konfigurationen möglich sind.
In dieser Arbeit werden beide Fragen durch geeignete mathematische Modellierung der Funkschnittstelle sowie des Funkzugangsnetzes (Radio Access Network) adressiert. Mithilfe der Warteschlangentheorie soll die stochastische Verteilung der (Ende-zu-Ende-) Latenz bestimmt werden. Dies liefert unterschiedliche stochastische Metriken, wie den Erwartungswert, die Varianz und insbesondere extrem hohe Perzentile am oberen Rand der Verteilung. Letztere geben schließlich Aufschluss über die gesuchten schlimmsten Fälle, die mit sehr geringer Wahrscheinlichkeit eintreten können. In der Arbeit werden Videostreaming und ein oder mehrere niedriglatente Anwendungen untersucht. Zu den wichtigsten Beiträgen zählt dabei die Entwicklung einer numerischen Methode, um die Latenz in allgemeinen Warteschlangensystemen für homogenen sowie für priorisierten heterogenen Datenverkehr zu bestimmen. Dies legt die Grundlage für die Analyse und Verbesserung von Ende-zu-Ende-Latenz für Anwendungen mit bekannten Verkehrsverteilungen in beliebigen Netzwerktopologien mit ein oder mehreren Slices
Flow-Level QoE of Video Streaming in Wireless Networks
International audienceThe Quality of Experience (QoE) of streaming service is often degraded by frequent play-back interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of initial delay. We study the QoE of streaming from the perspective of flow dynamics. Firstly, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We model the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs) for constant bit-rate (CBR) streaming. The explicit form starvation probabilities and mean start-up delay are obtained by use of a matrix function approach. Secondly, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station, and the playback variation of variable bit-rate (VBR) streaming. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the first moments such as the average throughput of opportunistic scheduling and the mean playback rate. While the variances of throughput and playback rate have very limited impact on starvation behavior in practice