Efficient data representation for XML in peerbased systems
Purpose New directions in the provision of enduser computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for dataintensive applications on such pl...
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Veröffentlicht in: | International journal of Web information systems 2010-06, Vol.6 (2), p.132-148 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose New directions in the provision of enduser computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for dataintensive applications on such platforms. The partitioned structure can be compressed using dictionarybased approaches and then directly queried without firstly decompressing the whole structure. Designmethodologyapproach The paper describes an architecture for partitioning XML into structural and dictionary elements and the subsequent manipulation of the dictionary elements to make the best use of available space. Findings The results indicate that considerable savings are available by removing duplicate dictionaries. The paper also identifies the most effective strategy for defining dictionary scope. Research limitationsimplications This evaluation is based on a range of benchmark XML structures and the approach to minimising dictionary size shows benefit in the majority of these. Where structures are small and regular, the benefits of efficient dictionary representation are lost. The authors' future research now focuses on heuristics for further partitioning of structural elements. Practical implications Mobile applications that need access to large data collections will benefit from the findings of this research. Traditional clientserver architectures are not suited to dealing with high volume demands from a multitude of small mobile devices. Peer data sharing provides a more scalable solution and the experiments that the paper describes demonstrate the most effective way of sharing data in this context. Social implications Many services are available via smartphone devices but users are wary of exploiting the full potential because of the need to conserve battery power. The approach mitigates this challenge and consequently expands the potential for users to benefit from mobile information systems. This will have impact in areas such as advertising, entertainment and education but will depend on the acceptability of file sharing being extended from the desktop to the mobile environment. Originalityvalue The original work characterises the most effective way of sharing large data sets between small mobile devices. This will save battery power on devices such as smartphones, thus providing benefits to users of such devices. |
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ISSN: | 1744-0084 |
DOI: | 10.1108/17440081011053122 |