DIMACS Working Group Meeting on Data Compression in Networks and Applications

March 18 - 20, 2002
DIMACS Center, Rutgers University, Piscataway, New Jersey

Adam Buchsbaum, AT&T Labs - Research, alb@research.att.com
S. Muthukrishnan, AT&T Labs - Research and Rutgers University, muthu@cs.rutgers.edu
Suleyman Cenk Sahinalp, Case Western Reserve University, cenk@eecs.cwru.edu
Jim Storer, Brandeis University, storer@cs.brandeis.edu
Jeff Vitter, Duke University, jsv@cs.duke.edu
Presented under the auspices of the Special Focus on Next Generation Networks Technologies and Applications and the Special Focus on Computational Information Theory and Coding.

Recent advances in compression span a wide range of applications. Homogeneous data sources invite specific compression methods, such as for Java bytecodes, XML data, WWW connectivity graphs, and tables of transaction data. WWW infrastructure also benefits from compression. Cache sharing proxies can exploit recent work on compressed Bloom filters. Search engines can extend the idea of sketches that work for text files to music data. Examples also abound in more heterogeneous domains, such as database compression, compression of biosequences and other biomedical data which are becoming of key importance in the context of telemedicine. Additionally, new general compression methods are always being developed, in particular those that allow indexing over compressed data or error resilience. The application of compression to new domains continues, e.g., the use of multicasting to reduce information communicated during parallel and distributed computing, and the installation of general compression methods deep in the network stack, allowing transparent, stream-level compression, independent of the application. Compression also inspires information theoretic tools for pattern discovery and classification, especially for biosequences.

This working group will explore the role of data compression in all layers of data networks, from the physical layer to the application and services layers, and address foundations and applied issues, as in (but not limited to) the examples above.

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Document last modified on January 3, 2002.