XML compression techniques: A survey and comparison

Sakr, Sherif

doi:10.1016/j.jcss.2009.01.004

Cited by 74 publications

(47 citation statements)

References 23 publications

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“…Later came compressors with query support such as XGrind (Tolani and Haritsa, 2002), XPRESS (Min et al, 2003) and XQzip (Cheng and Ng, 2004) (Sakr, 2009). These generic XML compressors performed worse when they were used for compressing GML.…”

Section: Literature Surveymentioning

confidence: 99%

Query Support for GMZ

Khandelwal

Rajan

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Generic text-based compression models are simple and fast but there are two issues that needs to be addressed. They cannot leverage the structure that exists in data to achieve better compression and there is an unnecessary decompression step before the user can actually use the data. To address these issues, we came up with GMZ, a lossless compression model aimed at achieving high compression ratios. The decision to design GMZ (Khandelwal and Rajan, 2017) exclusively for GML's Simple Features Profile (SFP) seems fair because of the high use of SFP in WFS and that it facilitates high optimisation of the compression model. This is an extension of our work on GMZ. In a typical server-client model such as Web Feature Service, the server is the primary creator and provider of GML, and therefore, requires compression and query capabilities. On the other hand, the client is the primary consumer of GML, and therefore, requires decompression and visualisation capabilities. In the first part of our work, we demonstrated compression using a python script that can be plugged in a server architecture, and decompression and visualisation in a web browser using a Firefox addon. The focus of this work is to develop the already existing tools to provide query capability to server. Our model provides the ability to decompress individual features in isolation, which is an essential requirement for realising query in compressed state. We construct an R-Tree index for spatial data and a custom index for non-spatial data and store these in a separate index file to prevent altering the compression model. This facilitates independent use of compressed GMZ file where index can be constructed when required. The focus of this work is the bounding-box or range query commonly used in webGIS with provision for other spatial and non-spatial queries. The decrement in compression ratios due to the new index file is in the range of 1-3 percent which is trivial considering the benefits of querying in compressed state. With around 75% average compression of the original data, query support in compressed state and decompression support in the browser, GMZ can be a good alternative to GML for WFS-like services.

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Section: Literature Surveymentioning

confidence: 99%

Query Support for GMZ

Khandelwal

Rajan

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…• XML compression 18 : This case study is based on the benchmark of XML compressors (e.g., XMill [24], Gzip, Bzip, XMLPPM [9]) that has been presented in [32]. In particular, this case study provides services for the implementation of nine XML compression tools with benchmarking tasks over a large XML corpus that covers the different types and scales of XML documents.…”

Section: Case Studiesmentioning

confidence: 99%

A Cloud-Based Platform for Democratizing and Socializing the Benchmarking Process

Bajaber¹,

Shafaat²,

Batarfi³

et al. 2016

ijacsa

Self Cite

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Abstract-Performances evaluation, benchmarking and reproducibility represent significant aspects for evaluating the practical impact of scientific research outcomes in the Computer Science field. In spite of all the benefits (e.g., increasing visibility, boosting impact, improving the research quality) which can be obtained from conducting comprehensive and extensive experimental evaluations or providing reproducible software artifacts and detailed description of experimental setup, the required effort for achieving these goals remains prohibitive. In this article, we present the design and the implementation details of the Liquid Benchmarking platform as a social and cloud-based platform for democratizing and socializing the software benchmarking processes. Particularly, the platform facilitates the process of sharing the experimental artifacts (computing resources, datasets, software implementations, benchmarking tasks) as services where the end users can easily design, mashup, execute the experiments and visualize the experimental results with zero installation or configuration efforts. Moreover, the social features of the platform enable the users to share and provide feedback on the results of the executed experiments in a form that can guarantee a transparent scientific crediting process. Finally, we present four benchmarking case studies that have been realized via the Liquid Benchmarking platform in the following domains: XML compression techniques, graph indexing and querying techniques, string similarity join algorithms and reverse K nearest neighbors algorithms.

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“…With reference to XML-based languages, several tools supporting efficient querying over compression schemes exists; see [7] for a comprehensive survey. XGrind [8] can perform (i) exact-match and prefix-match queries directly on compressed values and (ii) range and partial-match queries on values decompressed on-the-fly.…”

Section: B Related Workmentioning

confidence: 99%

A Framework for Query Processing over Compressed Knowledge Bases

Scioscia

Tinelli

2011

2011 IEEE 12th International Conference on Mobile Data Management

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Abstract-In semantic-based pervasive computing, annotated information is tied to micro-devices, such as RFID tags and wireless sensors, deployed in an environment. Compression techniques are essential, because of the verbosity of standard XMLbased languages for ontologies and semantic annotations. Beyond compression ratio, query efficiency is a key aspect. This paper presents a framework for querying knowledge bases expressed in OWL, serialized in RDF/XML syntax and compressed with a homomorphic encoding, in order to allow query evaluation without requiring decompression. Formalization of a significant set of queries demonstrates feasibility of the approach, while practical examples highlight its usefulness.

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XML compression techniques: A survey and comparison

Cited by 74 publications

References 23 publications

Query Support for GMZ

Query Support for GMZ

A Cloud-Based Platform for Democratizing and Socializing the Benchmarking Process

A Framework for Query Processing over Compressed Knowledge Bases

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