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dc.contributor.authorJacobsen, H. D.
dc.date.accessioned2016-05-10T20:16:55Zen
dc.date.available2016-05-10T20:16:55Zen
dc.date.issued1992-10en
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/608924en
dc.descriptionInternational Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, Californiaen_US
dc.description.abstractLempel-Ziv-Welch (LZW) algorithm is a popular data compaction technique that has been adopted by CCITT in its V.42bis recommendation and is often implemented in association with the V.32 standard for 9600 bps modems. It has also been implemented as Microcom Networking Protocol (MNP) Level 7, where it goes by the name of Enhanced Data Compression. LZW compacts data by encoding frequently occurring input strings with a single output symbol. The algorithm automatically generates a string dictionary for each symbol at each end of the transmission path. The amount of compaction that can be derived with the LZW algorithm varies with the type of data being transmitted and the efficiency by which table entries can be indexed. Table indexing is usually implemented by use of a hashing table. Although some manufacturers advertise a 4-to-1 gain in throughput, this seems to be an extreme case. This paper documents a implementation of the exact ZLW algorithm. The results presented in this paper are significantly less, typically on the order of 1-to-2 for ASCII text, with substantially less compaction for pre-compacted files or files containing random bit patterns. The efficiency of the LZW algorith on ASCII text is shown to be a function of dictionary size and block size. Although fewer transmitted symbols are required for larger dictionary tables, the additional bits required for the symbol index is marginally greater than the efficiency that is gained. The net effect is that dictionary sizes beyond 2K in size are increasingly less efficient for input data block sizes of 10K or more. The author concludes that the algorithm could be implemented as a direct table look-up rather than through a hashing algorithm. This would allow the LZW to be implemented with very simple firmware and with a maximum of hardware efficiency.
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.language.isoen_USen
dc.publisherInternational Foundation for Telemeteringen
dc.relation.urlhttp://www.telemetry.org/en
dc.rightsCopyright © International Foundation for Telemeteringen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectData Compression (Principal Topic)en
dc.subjectLempel-Ziv Algorithm (Primary Category)en
dc.titleSOME MEASURED PERFORMANCE BOUNDS AND IMPLEMENTATION CONSIDERATIONS FOR THE LEMPEL-ZIV-WELCH DATA COMPACTION ALGORITHMen_US
dc.typetexten
dc.typeProceedingsen
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
refterms.dateFOA2018-07-03T02:05:31Z
html.description.abstractLempel-Ziv-Welch (LZW) algorithm is a popular data compaction technique that has been adopted by CCITT in its V.42bis recommendation and is often implemented in association with the V.32 standard for 9600 bps modems. It has also been implemented as Microcom Networking Protocol (MNP) Level 7, where it goes by the name of Enhanced Data Compression. LZW compacts data by encoding frequently occurring input strings with a single output symbol. The algorithm automatically generates a string dictionary for each symbol at each end of the transmission path. The amount of compaction that can be derived with the LZW algorithm varies with the type of data being transmitted and the efficiency by which table entries can be indexed. Table indexing is usually implemented by use of a hashing table. Although some manufacturers advertise a 4-to-1 gain in throughput, this seems to be an extreme case. This paper documents a implementation of the exact ZLW algorithm. The results presented in this paper are significantly less, typically on the order of 1-to-2 for ASCII text, with substantially less compaction for pre-compacted files or files containing random bit patterns. The efficiency of the LZW algorith on ASCII text is shown to be a function of dictionary size and block size. Although fewer transmitted symbols are required for larger dictionary tables, the additional bits required for the symbol index is marginally greater than the efficiency that is gained. The net effect is that dictionary sizes beyond 2K in size are increasingly less efficient for input data block sizes of 10K or more. The author concludes that the algorithm could be implemented as a direct table look-up rather than through a hashing algorithm. This would allow the LZW to be implemented with very simple firmware and with a maximum of hardware efficiency.


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