4 research outputs found
A smartphone agent for QoE evaluation and user classification over mobile networks
The continuous growth of mobile users and bandwidth-consuming applications and the shortage of radio resources put a serious challenge on how to efficiently exploit existing networks and contemporary improve Quality of Experience. One of the most relevant problem for network operators is thus to find an explicit relationship between QoS and QoE, for the purpose of maximizing the latter while saving precious resources. In order to accomplish this challenging task, we present TeleAbarth, an innovative Android application entirely developed at TelecomItalia Laboratories, able to contemporary collect network measurements and end-users quality feedback regarding the use of smartphone applications. We deployed TeleAbarth in a field experimentation in order to study the relationship between QoS and QoE for video streaming applications, in terms of downstream bandwidth and video loading time. On the basis of the results obtained, we propose a technique to classify user behavior through his or her reliability, sensibility and fairness
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