SOME MEASURED PERFORMANCE BOUNDS AND IMPLEMENTATION CONSIDERATIONS FOR THE LEMPEL-ZIV-WELCH DATA COMPACTION ALGORITHM

• Main Author: Jacobsen, H. D.
• Language: en_US
• Published: International Foundation for Telemetering 1992
• Subjects: Data Compression (Principal Topic); Lempel-Ziv Algorithm (Primary Category)
• Online Access: http://hdl.handle.net/10150/608924; http://arizona.openrepository.com/arizona/handle/10150/608924

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California === Lempel-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.