Conference Paper

Fine grained content-based adaptation mechanism for providing high end-user quality of experience with adaptive hypermedia systems.

DOI: 10.1145/1135777.1135790 Conference: Proceedings of the 15th international conference on World Wide Web, WWW 2006, Edinburgh, Scotland, UK, May 23-26, 2006
Source: DBLP

ABSTRACT New communication technologies can enable Web users to access personalised information "anytime, anywhere". However, the network environments allowing this "anytime, anywhere" access may have widely varying performance characteristics such as bandwidth, level of congestion, mobility support, and cost of transmission. It is unrealistic to expect that the quality of delivery of the same content can be maintained in this variable environment, but rather an effort must be made to fit the content served to the current delivery conditions, thus ensuring high Quality of Experience (QoE) to the users. This paper introduces an end-user QoE-aware adaptive hypermedia framework that extends the adaptation functionality of adaptive hypermedia systems with a fine-grained content-based adaptation mechanism. The proposed mechanism attempts to take into account multiple factors affecting QoE in relation to the delivery of Web content. Various simulation tests investigate the performance improvements provided by this mechanism, in a home-like, low bit rate operational environment, in terms of access time per page, aggregate access time per browsing session and quantity of transmitted information.

  • [Show abstract] [Hide abstract]
    ABSTRACT: This chapter discusses how the trails concept can be applied in providing personalised learning, with a focus on the use of trails in adaptive e-learning systems which adjust their behaviour in order to better cater for individual learners' needs. The first half of the chapter looks at some of the technological and theoretical issues posed by personalised trails: We present a generic architecture for personalisation which can potentially be deployed on a variety of hardware configurations, and then look at learner profiling, a key aspect of personalisation. Learner profiles store the information about learners that is used to provide personalisation, so the structure and content of the learner profile used by a system has implications for the kinds of personalisation and support for trails that can be provided. In this context we see how Semantic Web technologies can potentially be used to integrate disparate user profile specifications. In the second half of the chapter we look at the practicalities and practice of personalising trails in the context of e-learning. After a brief general discussion of some techniques that can be used to provide personalisation we use examples of real systems to demonstrate the potential for providing personalised trail support that currently exists. As well as systems that provide trails for learners our examples include adaptive hypertext techniques which provide a kind of trail support through adaptive presentation; systems that provide adaptive feedback to learners and which put learners in direct control of the adaptivity; social navigation systems and mobile computing systems. We conclude with some thoughts about the future of this burgeoning research area.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Efficient bandwidth estimation is significant for Quality of Service (QoS) of multimedia services in IEEE 802.11 WLANs. Many bandwidth estimation solutions have been developed such as probing-based technique and cross-layer scheme. However, these solutions either introduce additional traffic or require modification to the standard protocols. This paper develops a model based bandwidth estimation algorithm at application layer when TCP traffic is delivered in the IEEE 802.11 networks. The proposed model firstly considers both TCP congestion control mechanism and IEEE 802.11 contention-based channel access mechanism. The bandwidth estimation process at the server estimates the achievable bandwidth using two types of parameters: data size to be sent and the feedback information from receivers, i.e. packet loss rate and the number of clients. The two tailed T-test analysis demonstrates that there is a 95% confidence level that there is no statistical difference between the results from the proposed bandwidth estimation algorithm and the results from the real test. Additionally, the proposed algorithm achieves higher accuracy and lower standard deviation of bandwidth, in comparison with other state-of-the art bandwidth estimation schemes.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel authoring framework for Quality of Ex-perience (QoE) aware Adaptive Hypermedia Systems. It extends the LAOS au-thoring model in order to consider delivery performance issues. The paper formalises and exemplifies the newly proposed QoE extensions for the LAOS Adaptation and Presentation Models that include QoE Characteristics and QoE Rules layers.


Available from