Quality of experience aware adaptive hypermedia system

The research reported in this thesis proposes, designs and tests a novel Quality of Experience Layer (QoE-layer) for the classic Adaptive Hypermedia Systems (AHS) architecture. Its goal is to improve the end-user perceived Quality of Service in different operational environments suitable for residential users. While the AHS’ main role of delivering personalised content is not altered, its functionality and performance is improved and thus the user satisfaction with the service provided. The QoE Layer takes into account multiple factors that affect Quality of Experience (QoE), such as Web components and network connection. It uses a novel Perceived Performance Model that takes into consideration a variety of performance metrics, in order to learn about the Web user operational environment characteristics, about changes in network connection and the consequences of these changes on the user’s quality of experience. This model also considers the user’s subjective opinion about his/her QoE, increasing its effectiveness and suggests strategies for tailoring Web content in order to improve QoE. The user related information is modelled using a stereotype-based technique that makes use of probability and distribution theory. The QoE-Layer has been assessed through both simulations and qualitative evaluation in the educational area (mainly distance learning), when users interact with the system in a low bit rate operational environment. The simulations have assessed “learning” and “adaptability” behaviour of the proposed layer in different and variable home connections when a learning task is performed. The correctness of Perceived Performance Model (PPM) suggestions, access time of the learning process and quantity of transmitted data were analysed. The results show that the QoE layer significantly improves the performance in terms of the access time of the learning process with a reduction in the quantity of data sent by using image compression and/or elimination. A visual quality assessment confirmed that this image quality reduction does not significantly affect the viewers’ perceived quality that was close to “good” perceptual level. For qualitative evaluation the QoE layer has been deployed on the open-source AHA! system. The goal of this evaluation was to compare the learning outcome, system usability and user satisfaction when AHA! and QoE-ware AHA systems were used. The assessment was performed in terms of learner achievement, learning performance and usability assessment. The results indicate that QoE-aware AHA system did not affect the learning outcome (the students have similar-learning achievements) but the learning performance was improved in terms of study time. Most significantly, QoE-aware AHA provides an important improvement in system usability as indicated by users’ opinion about their satisfaction related to QoE

Preliminary Measurements on the Effect of Server Adaptation for Web Content Delivery

A Web client experiences poor performance due to low bandwidth, high latency, network congestion, etc. A server can select a lower quality version of the resource or alter the manner of content delivery to improve performance. We present early measurement results on the actual latency reduction for a wide class of real and geographically dispersed set of clients. Earlier research work in compression, delta encoding, use of content distribution networks (CDNs), etc. has examined Web performance via the lens of individual improvements in reducing user-perceived latency or load on servers. They use different methodologies, workloads, and validation techniques. We examine multiple performance related factors in a single unified framework, a set of server actions to improve performance, and use a canonical set of container documents with various distributions of embedded objects in terms of number and size. Our work can be applied by a variety of sites to test the potential i

Preliminary Measurements on the Effect of Server Adaptation for Web Content Delivery

INTRODUCTION A Web client experiences poor performance due to low bandwidth, high latency, network congestion, etc. A server can select a lower quality version of the resource or alter manner of content delivery to improve performance. Here, we present early measurement results on the actual latency reduction for a wide class of real and geographically dispersed set of clients. Earlier research work in compression, delta encoding, use of content distribution networks (CDNs), etc. has examined Web performance via the lens of individual improvements in reducing userperceived latency or load on servers. They use different methodologies, workloads, and validation techniques. We examine multiple performance related factors in a single unified framework, a set of server actions to improve performance, and use a canonical set of container documents with various distributions of embedded objects in terms of number and size. Our work can be applied by a variety of sites to test the potential

Quality-oriented adaptation scheme for multimedia streaming in local broadband multi-service IP networks

The research reported in this thesis proposes, designs and tests the Quality-Oriented Adaptation Scheme (QOAS), an application-level adaptive scheme that offers high quality multimedia services to home residences and business premises via local broadband IP-networks in the presence of other traffic of different types. QOAS uses a novel client-located grading scheme that maps some network-related parameters’ values, variations and variation patterns (e.g. delay, jitter, loss rate) to application-level scores that describe the quality of delivery. This grading scheme also involves an objective metric that estimates the end-user perceived quality, increasing its effectiveness. A server-located arbiter takes content and rate adaptation decisions based on these quality scores, which is the only information sent via feedback by the clients. QOAS has been modelled, implemented and tested through simulations and an instantiation of it has been realized in a prototype system. The performance was assessed in terms of estimated end-user perceived quality, network utilisation, loss rate and number of customers served by a fixed infrastructure. The influence of variations in the parameters used by QOAS and of the networkrelated characteristics was studied. The scheme’s adaptive reaction was tested with background traffic of different type, size and variation patterns and in the presence of concurrent multimedia streaming processes subject to user-interactions. The results show that the performance of QOAS was very close to that of an ideal adaptive scheme. In comparison with other adaptive schemes QOAS allows for a significant increase in the number of simultaneous users while maintaining a good end-user perceived quality. These results are verified by a set of subjective tests that have been performed on viewers using a prototype system