Summary form only given. The unbounded version of the LZ2 compression method is P-complete, therefore, it is unlikely to have a sublinear work space when LZ2 compression is implemented unless a deletion heuristic is applied to bound the dictionary. Several LZ2 compression heuristics have been designed and several deletion heuristics have been applied. In this work, we show experimental results on the compression effectiveness for 2/spl les/p/spl les/6, using the AP compression heuristic. The relaxed LRU (RLRU) deletion heuristic turns out to be as good as LRU even when p is equal to 2. This fact shows that there should be always an improvement when the two values of p differ substantially. FREEZE, RESTART and SWAP are simpler heuristics, which do not delete elements from the dictionary at each step. SWAP is the best among these simpler approaches and has a worse compression efficiency than RLRU and LRU.
[1]
Sergio De Agostino.
P-complete Problems in Data Compression
,
1994,
Theor. Comput. Sci..
[2]
James A. Storer,et al.
Data Compression: Methods and Theory
,
1987
.
[3]
James A. Storer.
Massively Parallel Systolic Algorithms for Real-Time Dictionary-Based Text Compression
,
1992
.
[4]
Sergio De Agostino,et al.
Bounded size dictionary compression: SCk-completeness and NC algorithms
,
2003,
Inf. Comput..
[5]
Abraham Lempel,et al.
Compression of individual sequences via variable-rate coding
,
1978,
IEEE Trans. Inf. Theory.