Transcoding: Extending e-business to new environments

Abstract

The promise of e-business is coming true: both businesses and individuals are using the Web to buy products and services. Both want to extend the reach of e-business to new environments. Customers want to check accounts, access information, and make purchases with their cellular phones, pagers, and personal digital assistants (PDAs). Banks, airlines, and retailers are competing to provide the most ubiquitous, convenient service for their customers. Web applications designed to take advantage of the rich rendering capabilities of advanced desktop browsers on large displays do not generally render effectively on the small screens available on phones and PDAs. Some devices have little or no graphics capability, or they require different markup languages, such as Wireless Markup Language (WML), for text presentation. Transcoding is technology for adapting content to match constraints and preferences associated with specific environments. This paper compares and contrasts different approaches to content adaptation, including authoring different versions to accommodate different environments, using application server technology such as JavaServer pages TM (JSP TM) to create multiple versions of dynamic applications, and dynamically transcoding information generated by a single application. For dynamic transcoding, the paper describes several different transcoding methodologies employed by the IBM WebSphere TM Transcoding Publisher product, including HyperText Markup Language (HTML) simplification, Extensible Markup Language stylesheet selection and application, HTML conversion to WML, WML deck fragmentation, and image transcoding. The paper discusses how to decide whether transcoding should be performed at the content source or in a network intermediary. It also describes a means of identifying the device and network characteristics associated with a request and using that information to decide how to transcode the response. Finally, the paper discusses the need for new networking benchmarks to characterize the server load and performance characteristics for dynamic transcoding.

Correlation-Based Content Adaptation for Mobile Web Browsing

“…We designed the all-in algorithm 1 for use when only one-sided feedback is available, and investigate it in the context of image fidelity adaptation. The algorithm starts off by using the standard K-means clustering algorithm to partition users into multiple groups.…”

“…There is significant research on content adaptation for mobile devices [1,2,3,4,5,6,8,9,10,17,18,19,20], and even a few commercial adaptation systems have been deployed [1,21].…”

“…A promising solution to these problems is adaptation middleware, interposed in the network path between the client and web server, which automatically tailors content for individual mobile devices [1,2,3,4,5,6,7,8,9,10]. For example, images on web pages can be served to the user at a reduced fidelity in order to conserve bandwidth and energy, and improve download times.…”

Dialog Model Clustering for User Interface Adaptation

“…This process is called paginating and chunking [9]. Pagination is similar to the fragmentation process in IBM's Websphere [10]. The places where the process of pagination cuts a Web forms into two different pages depends on the device screen's size requirements, but not on semantic dependencies between controls.…”

Towards Highly Adaptive Services for Mobile Computing

“…However, our fi-amework provides a finer control on profile aggregation, and includes a policy mechanism. Various other architectures address the problem of service adaptation in mobile environments [2,7,9,11,14,21]. The distinguishing feature of our architecture is that in our case the adaptation process is driven by the evaluation of distributed profile data and policies which are stored on and handled by modules in the trusted domain of their data source.…”