A Context-Aware Decision Engine for Content Adaptation

M obile-device users often wish that they could access the variety of rich hypermedia content that exists or will exist on the Web. Given, however, these devices' constrained computational and rendering power and cellular networks' limited bandwidth, effective Web content presentation will require new computation patterns. The mismatch between rich multimedia content and constrained client capability presents a research challenge. Mobile devices' variety also increases the difficulty of accessing content. For example, mobile devices are conveniently sized to fit in a pocket, but this size constrains their display area. 1 Creating trimmed versions of content could get around this constraint, but differences in display capabilities would easily make a device-specific authoring approach too costly to be practical. 2 Examples of device differences include screen sizes ranging from 20 × 5 characters to thousands of pixels, and color depths ranging from two-line black-and-white display to full-color display. 3 Web content can also be encoded in many different modes, such as JPEG, which best suits PCs, and the 1-bit WBMP format for Wireless Application Protocol (WAP) devices. Furthermore, mobile devices support many different markup languages, including HTML, HDML (Handheld Device Markup Language), and WML (Wireless Markup Language). If the client device subscribes to a Web site that uses a presentational mode that the device cannot render, information loss might result. While users complain about the " World Wide Wait " problem, owing partly to slow last-mile speeds, cellular networks work at far lower data rates, which work fine for plain text but are far from adequate for Web pages. 4 Much Internet content and various other types of multimedia information that mobile applications running on PDAs or notebooks use, such as for identifying locations (for example, the nearest restaurant) or describing product displays (for stock inventory), are unsuitable for smaller devices such as WAP phones. To tackle these problems, we propose a content adaptation system. Such a system decides the optimal content version for presentation and the best strategy for deriving that version, and then generates that version. The system's most crucial component is the decision engine, which negotiates for that strategy. The engine takes into account the entire computing context (see the " Context Awareness " sidebar), focusing particularly on the user's preferences. A prototype PDF document adaptation system demonstrates our approach's viability. The process begins when someone uses a mobile device to submit a request to the system—that is, to …