Real-time and distributed applications for dictionary-based data compression

The greedy approach to dictionary-based static text compression can be executed by a finite state machine. When it is applied in parallel to different blocks of data independently, there is no lack of robustness even on standard large scale distributed systems with input files of arbitrary size. Beyond standard large scale, a negative effect on the compression effectiveness is caused by the very small size of the data blocks. A robust approach for extreme distributed systems is presented in this paper, where this problem is fixed by overlapping adjacent blocks and preprocessing the neighborhoods of the boundaries. Moreover, we introduce the notion of pseudo-prefix dictionary, which allows optimal compression by means of a real-time semi-greedy procedure and a slight improvement on the compression ratio obtained by the distributed implementations.