Adapting to network and client variability via on-demand dynamic distillation

  • Authors:

  • Armando Fox;Steven D. Gribble;Eric A. Brewer;Elan Amir

  • Affiliations:

  • University of California at Berkeley;University of California at Berkeley;University of California at Berkeley;University of California at Berkeley

  • Venue:
  • Proceedings of the seventh international conference on Architectural support for programming languages and operating systems
  • Year:
  • 1996

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Abstract

The explosive growth of the Internet and the proliferation of smart cellular phones and handheld wireless devices is widening an already large gap between Internet clients. Clients vary in their hardware resources, software sophistication, and quality of connectivity, yet server support for client variation ranges from relatively poor to none at all. In this paper we introduce some design principles that we believe are fundamental to providing "meaningful" Internet access for the entire range of clients. In particular, we show how to perform on-demand datatype-specific lossy compression on semantically typed data, tailoring content to the specific constraints of the client. We instantiate our design principles in a proxy architecture that further exploits typed data to enable application-level management of scarce network resources. Our proxy architecture generalizes previous work addressing all three aspects of client variation by applying well-understood techniques in a novel way, resulting in quantitatively better end-to-end performance, higher quality display output, and new capabilities for low-end clients.