Optimizing XML Compression

TL;DR

This paper investigates XML compression, demonstrating that optimizing compression configurations is NP-hard, and proposes an approximation algorithm for partitioning document content to improve compression gain.

Contribution

It formally proves the NP-hardness of optimizing XML compression configurations and introduces a branch-and-bound based approximation algorithm for content partitioning.

Findings

Optimal compression configuration problem is NP-hard.

Proposed approximation algorithm improves compression partitioning.

Analysis guides better XML compression strategies.

Abstract

The eXtensible Markup Language (XML) provides a powerful and flexible means of encoding and exchanging data. As it turns out, its main advantage as an encoding format (namely, its requirement that all open and close markup tags are present and properly balanced) yield also one of its main disadvantages: verbosity. XML-conscious compression techniques seek to overcome this drawback. Many of these techniques first separate XML structure from the document content, and then compress each independently. Further compression gains can be realized by identifying and compressing together document content that is highly similar, thereby amortizing the storage costs of auxiliary information required by the chosen compression algorithm. Additionally, the proper choice of compression algorithm is an important factor not only for the achievable compression gain, but also for access performance. Hence, choosing a compression configuration that optimizes compression gain requires one to determine (1) a partitioning strategy for document content, and (2) the best available compression algorithm to apply to each set within this partition. In this paper, we show that finding an optimal compression configuration with respect to compression gain is an NP-hard optimization problem. This problem remains intractable even if one considers a single compression algorithm for all content. We also describe an approximation algorithm for selecting a partitioning strategy for document content based on the branch-and-bound paradigm.