TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Safieh, Malek
A1  - Freudenberger, Jürgen
T1  - Address space partitioning for the parallel dictionary LZW data compression algorithm
T2  - 16th Canadian Workshop on Information Theory (CWIT 2019), June 2-5, Hamilton, Ontario, Canada
N2  - The Lempel-Ziv-Welch (LZW) algorithm is an important dictionary-based data compression approach that is used in many communication and storage systems. The parallel dictionary LZW (PDLZW) algorithm speeds up the LZW encoding by using multiple dictionaries. The PDLZW algorithm applies different dictionaries to store strings of different lengths, where each dictionary stores only strings of the same length. This simplifies the parallel search in the dictionaries for hardware implementations. The compression gain of the PDLZW depends on the partitioning of the address space, i.e. on the sizes of the parallel dictionaries. However, there is no universal partitioning that is optimal for all data sources. This work proposes an address space partitioning technique that optimizes the compression rate of the PDLZW using a Markov model for the data. Numerical results for address spaces with 512, 1024, and 2048 entries demonstrate that the proposed partitioning improves the performance of the PDLZW compared with the original proposal.
Y1  - 2019
UR  - https://ieeexplore.ieee.org/document/8929928
SN  - 978-1-7281-0954-1
SB  - 978-1-7281-0954-1
U6  - https://doi.org/10.1109/CWIT.2019.8929928
DO  - https://doi.org/10.1109/CWIT.2019.8929928
N1  - Volltextzugriff für Angehörige der Hochschule Konstanz via Datenbank IEEE Xplore möglich
SP  - 6
S1  - 6
PB  - IEEE
ER  -