Content adaptation is a crucial step in making desktop-oriented Web resources available to mobile, small device users. In this paper, we propose a decision engine comprising a content analysis module and a negotiation module to serve as the core of a content adaptation architecture. The content analysis module parses a structured Web document originally intended for the desktop into small sections and transforms the document into a form that is best suited for rendering in a constrained mobile device. The transformation also provides the user with the best content value in an adapted Web page while preserving content integrity. With the transformed document, the negotiation module selects the best rendering parameters to be used in the synthesis of an optimal adapted version of the content. The decisions made are based on the user's preference and QoS considerations. We have built a prototype to demonstrate the viability of our approach.

We address the challenges of building a good content adaptation service for mobile devices and propose a decision engine that is user-centric with QoS awareness, which can automatically negotiate for the appropriate adaptation decision to use in the synthesis of an optimal adapted version. The QoS-sensitive approach complements the lossy nature of the transcoding operations. The decision engine will look for the best trade off among various parameters in order to reduce the loss of quality in various domains. Quantitative methods are suggested to measure the QoS of the content versions in various quality domains. Based on the particular user perception and other contextual information on the client capability, the network connection, and the requested content, the proposed negotiation algorithm will determine a content version with a good aggregate score. We have built a prototype document adaptation system for PDF documents to demonstrate the viability of our approach.

We propose a decision engine with QoS awareness that can automatically negotiate for the appropriate adaptation strategies to be used to produce an optimal adapted version. The QoS-sensitive approach complements the lossy nature of the transcoding operations. The decision engine will look for the best tradeoff among various parameters in order to reduce the loss of quality, in various domains. Quantitative methods are suggested to measure the QoS of the content versions. Based on the particular user perception of these quality domains and other context information on the client capability, the proposed negotiation algorithm will determine a content version with a good aggregate score. We study factors such as processing overhead and the optimization accuracy of the algorithm, and their tradeoff. We built a prototype document adaptation system for PDF documents to demonstrate the viability of our approach.

We propose a method that can find the optimal tradeoff point between transcoding overhead (CPU cost) and storage needed for the various pre-processed content variants (I/O cost). The method selectively pre-adapts a subset of content variants and leaves the generation of the residue to dynamic content adaptation with this pre-adapted subset as an input. We prove bounds regarding the optimality of the algorithm employed. The proposed model creates a collaborative environment across the components of client, proxy and server, based on which we study the distribution of adaptation complexity across these components. We use simulation to verify the projected benefits. The method has been successfully implemented in a trial PDF document content adaptation system.