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Open AccessArticle

Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files

Computer Science Department, Sapienza University of Rome, Rome 00185, Italy
Dipartmento di Informatica, Università di Salerno, Fisciano (SA) 84084, Italy
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in International Conference on Data Compression, Communication Processing and Security 2016.
Academic Editor: Spyros Kontogiannis
Algorithms 2017, 10(1), 21;
Received: 25 November 2016 / Revised: 24 December 2016 / Accepted: 23 January 2017 / Published: 28 January 2017
(This article belongs to the Special Issue Data Compression, Communication Processing and Security 2016)
PDF [236 KB, uploaded 4 February 2017]


Broadcasting a message from one to many processors in a network corresponds to concurrent reading on a random access shared memory parallel machine. Computing the trees of a forest, the level of each node in its tree and the path between two nodes are problems that can easily be solved with concurrent reading in a time logarithmic in the maximum height of a tree. Solving such problems with exclusive reading requires a time logarithmic in the number of nodes, implying message passing between disjoint pairs of processors on a distributed system. Allowing concurrent reading in parallel algorithm design for distributed computing might be advantageous in practice if these problems are faced on shallow trees with some specific constraints. We show an application to LZC (Lempel-Ziv-Compress)-compressed file decoding, whose parallelization employs these computations on such trees for realistic data. On the other hand, zipped files do not have this advantage, since they are compressed by the Lempel–Ziv sliding window technique. View Full-Text
Keywords: LZ compression; decoding; pram; mapreduce LZ compression; decoding; pram; mapreduce
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Agostino, S.D.; Carpentieri, B.; Pizzolante, R. Concurrent vs. Exclusive Reading in Parallel Decoding of LZ-Compressed Files. Algorithms 2017, 10, 21.

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