FibLSS: A Scalable Label Storage Scheme for Dynamic XML Updates

O’Connor, Martin F.; Roantree, Mark

doi:10.1007/978-3-642-40683-6_17

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…In other words, not only labels should have variable sizes but also the length field of the labels should be stored, and be identified, using a variable length scheme. Thus, we store each label's length using the encoding method called FibLSS [43] along with the label itself, just before it.…”

Section: Proposed Methodsmentioning

confidence: 99%

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A new effective method for labeling dynamic XML data

Khanjari

Gaeini

2018

J Big Data

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IntroductionXML is a semi-structural and standard document format to exchange data. Elements in XML documents are regular and there are structural relationships between them [1]. In fact, processing queries in XML should recognize these structural relationships. They also should determine the order of elements in a document. Node labeling in XML data is one way to increase the efficiency of query processing. Labeling means allocating a unique identifier to each node in XML documents [2]. A labeling scheme encompasses traversal or browsing the document, analyzing the elements, and assessing available relationships between elements. So, it should generate small enough labels in order to be processed efficiently both in initial label assigning as well as when queries are issued.A challenging problem of the existing labeling schemes is the need for relabeling nearly all the existing nodes after inserting new nodes in XML documents. While update in XML data is a usual operation in many real-world applications, e.g. stream data, relabeling will influence the query performance, especially when large-size labels are assigned Abstract Query processing based on labeling dynamic XML documents has gained more attention in the past several years. An efficient labeling scheme should provide small size labels keeping the simplicity of the exploited algorithm in order to avoid complex computations as well as retaining the readability of structural relationships between nodes. Moreover, for dynamic XML data, relabeling the nodes in XML updates should be avoided. However, the existing schemes lack the capability of supporting all of these requirements. In this paper, we propose a new labeling scheme which assigns variable-length labels to nodes in dynamic XML documents. Our method employs the FibLSS encoding scheme that exploits the properties of the Fibonacci sequence to provide variable-length node labels of appropriate size. In XML updating process, we add a new section only in the new node's label without relabeling the existing nodes while keeping the order of nodes as well as preserving the structural relationships. Our labeling method is scalable as it is not subject to overflow, and as the number of nodes to be labeled increases exponentially, the size of labels grows linearly, which makes it suitable for big datasets. It also has the best performance in computational processing costs compared to existing approaches. The results of the experiments confirm the advantages of our proposed method in comparison to state-of-the-art techniques.

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Section: Proposed Methodsmentioning

confidence: 99%

“…Note that, this is the total storage which is needed in the worst case. However, for the average case, as the number nodes to be encoded using the FibLSS encoding increases exponentially, the growth rate in the number of bits required to encode nodes is linear [43].…”

Section: Label Size Analysismentioning

confidence: 99%

A new effective method for labeling dynamic XML data

Khanjari

Gaeini

2018

J Big Data

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XML Labels Compression using Prefix-encodings

Zadjali¹,

North

2016

Proceedings of the 12th International Conference on Web Information Systems and Technologies

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Abstract:XML is the de-facto standard for data representation and communication over the web, and so there is a lot of interest in querying XML data and most approaches require the data to be labelled to indicate structural relationships between elements. This is simple when the data does not change but complex when it does. In the day-to-day management of XML databases over the web, it is usual that more information is inserted over time than deleted. Frequent insertions can lead to large labels which have a detrimental impact on query performance and can cause overflow problems. Many researchers have shown that prefix encoding usually gives the highest compression ratio in comparison to other encoding schemes. Nonetheless, none of the existing prefix encoding methods has been applied to XML labels. This research investigates compressing XML labels via different prefix-encoding methods in order to reduce the occurrence of any overflow problems and improve query performance. The paper also presents a comparison between the performances of several prefix-encodings in terms of encoding/decoding time and compressed code size.

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FibLSS: A Scalable Label Storage Scheme for Dynamic XML Updates

Cited by 2 publications

References 20 publications

A new effective method for labeling dynamic XML data

A new effective method for labeling dynamic XML data

XML Labels Compression using Prefix-encodings

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