Reusable Prime Number Labeling Scheme for Hierarchical Data Representation in Relational Databases

Hierarchical data structures are important for many computing and information science disciplines including data mining, terrain modeling, and image analysis. There are many specialized hierarchical data management systems, but they are not always available. Alternatively, relational databases are far more common and offer superior reliability, scalability, and performance. However, relational databases cannot natively store and manage hierarchical data. Labeling schemes resolve this issue by labeling all nodes with alphanumeric strings that can be safely stored and retrieved from a database. One such scheme uses prime numbers for its labeling purposes, however the performance and space utilization of this method are not optimal. We propose a more efficient and compact version of this approach

Reuse or Never Reuse the Deleted Labels in XML Query Processing Based on Labeling Schemes

Abstract. To facilitate the XML query processing, several kinds of labeling schemes have been proposed. Based on the labeling schemes, the ancestordescendant and parent-child relationships in XML queries can be quickly determined without accessing the original XML file. Recently, more researches are focused on how to update the labels when nodes are inserted into the XML. However how to process the deleted labels are not discussed previously. We think that the deleted labels can be processed in two different directions: (1) reuse all the deleted labels to control the label size increasing speed and improve the query performance; (2) never reuse the deleted labels to query different versions of the XML data based on labeling schemes. In this paper, we firstly introduce our previous work, called QED, which can completely avoid the relabeling in XML updates. Secondly based on QED we propose a new algorithm, called Reuse, which can reuse all the deleted labels to control the label size increasing speed; meanwhile the Reuse algorithm can completely avoid the re-labeling also. Thirdly to query different versions of the XML data, we propose another new algorithm, called NeverReuse, which is the only approach that never reuses any deleted labels. Extensive experimental results show that the algorithms proposed in this paper can control the label size increasing speed when reusing all the deleted labels, and is the only approach to query different versions of the XML data based on labeling schemes.

Dynamic Containment Labeling Scheme for XML

提出了适用于XMl文档更新环境下的区间编码方法——dClS(dynAMIC COnTAInMEnT lAbElIng SCHEME).dClS将基于整数的编码泛化到基于向量的编码,扩展了传统静态区间编码方法,有效避免了XMl文档更新时的重新编码.不论文档更新与否,dClS都显示了良好的性能:dClS利用基于整数的静态区间编码方法进行初始编码,在文档不更新的环境下,具有较高的存储效率和查询性能;同时,dClS将整数视为特殊向量,不仅能够支持文档更新,而且更新效率高;特别是倾斜插入时,dClS可以避免编码位长的快速增加.实验结果表明,与已有的动态区间编码方法相比,dClS具有更好的性能.A novel containment scheme called DCLS is proposed to effectively process updates in dynamic XML data.DCLS generalizes the static containment scheme from integer order to vector order and thus completely avoids re-labeling when XML data updating.Moreover,DCLS is compact and efficient regardless of whether the documents are updated or not.On the one hand,DCLS uses integer-based static containment scheme for initial labeling,which yields compact size and excellent query efficiency for static documents.On the other hand,DCLS takes the integer as special vector,which not only deals with the case of document updating,but also achieves high query performance.Most importantly,DCLS can effectively avoid the rapid increase of labeling size for the case of skewed insertions.Experimental results confirm the benefits of this approach compared to previous dynamic containment schemes.国家自然科学基金(50604012);中央高校基本科研业务费专项资金(2011121049

Prime Number-Based Hierarchical Data Labeling Scheme for Relational Databases

Hierarchical data structures are an important aspect of many computer science fields including data mining, terrain modeling, and image analysis. A good representation of such data accurately captures the parent-child and ancestor-descendent relationships between nodes. There exist a number of different ways to capture and manage hierarchical data while preserving such relationships. For instance, one may use a custom system designed for a specific kind of hierarchy. Object oriented databases may also be used to model hierarchical data. Relational database systems, on the other hand, add an additional benefit of mature mathematical theory, reliable implementations, superior functionality and scalability. Relational databases were not originally designed with hierarchical data management in mind. As a result, abstract information can not be natively stored in database relations. Database labeling schemes resolve this issue by labeling all nodes in a way that reveals their relationships. Labels usually encode the node's position in a hierarchy as a number or a string that can be stored, indexed, searched, and retrieved from a database. Many different labeling schemes have been developed in the past. All of them may be classified into three broad categories: recursive expansion, materialized path, and nested sets. Each model has its strengths and weaknesses. Each model implementation attempts to reduce the number of weaknesses inherent to the respective model. One of the most prominent implementations of the materialized path model uses the unique characteristics of prime numbers for its labeling purposes. However, the performance and space utilization of this prime number labeling scheme could be significantly improved. This research introduces a new scheme called reusable prime number labeling (rPNL) that reduces the effects of the mentioned weaknesses. The proposed scheme advantage is discussed in detail, proven mathematically, and experimentally confirmed

Querying and Updating XML Data based on Node Labeling Schemes

Ph.DDOCTOR OF PHILOSOPH

Pentagonal scheme for dynamic XML prefix labelling

In XML databases, the indexing process is based on a labelling or numbering scheme and generally used to label an XML document to perform an XML query using the path node information. Moreover, a labelling scheme helps to capture the structural relationships during the processing of queries without the need to access the physical document. Two of the main problems for labelling XML schemes are duplicated labels and the cost efficiency of labelling time and size. This research presents a novel dynamic XML labelling scheme, called the Pentagonal labelling scheme, in which data are represented as ordered XML nodes with relationships between them. The update of these nodes from large scale XML documents has been widely investigated and represents a challenging research problem as it means relabelling a whole tree. Our algorithms provide an efficient dynamic XML labelling scheme that supports data updates without duplicating labels or relabelling old nodes. Our work evaluates the labelling process in terms of size and time, and evaluates the labelling scheme’s ability to handle several insertions in XML documents. The findings indicate that the Pentagonal scheme shows a better initial labelling time performance than the compared schemes, particularly when using large XML datasets. Moreover, it efficiently supports random skewed updates, has fast calculations and uncomplicated implementations so efficiently handles updates. Also, it proved its capability in terms of the query performance and in determining the relationships.Libyan governmen

Clustering-based Labelling Scheme - A Hybrid Approach for Efficient Querying and Updating XML Documents

Extensible Markup Language (XML) has become a dominant technology for transferring data through the worldwide web. The XML labelling schemes play a key role in handling XML data efficiently and robustly. Thus, many labelling schemes have been proposed. However, these labelling schemes have limitations and shortcomings. Thus, the aim of this research was to investigate the existing XML labelling schemes and their limitations in order to address the issue of efficiency of XML query performance. This thesis investigated the existing labelling schemes and classified them into three categories based on certain criteria, in order to identify the limitations and challenges of these labelling schemes. Based on the outcomes of this investigation, this thesis proposed a state-of-theart labelling scheme, called clustering-based labelling scheme, to resolve or improve the key limitations such as the efficiency of the XML query processing, labelling XML nodes, and XML updates cost. This thesis argued that using certain existing labelling schemes to label nodes, and using the clustering-based techniques can improve query and labelling nodes efficiency. Theoretically, the proposed scheme is based on dividing the nodes of an XML document into clusters. Two existing labelling schemes, which are the Dewey and LLS labelling schemes, were selected for labelling these clusters and their nodes. Subsequently, the proposed scheme was designed and implemented. In addition, the Dewey and LLS labelling scheme were implemented for the purpose of evaluating the proposed scheme. Subsequently, four experiments were designed in order to test the proposed scheme against the Dewey and LLS labelling schemes. The results of these experiments suggest that the proposed scheme achieved better results than the Dewey and LLS schemes. Consequently, the research hypothesis was accepted overall with few exceptions, and the proposed scheme showed an improvement in the performance and all the targeted features and aspects

Labelling Dynamic XML Documents: A GroupBased Approach

Documents that comply with the XML standard are characterised by inherent ordering and their modelling usually takes the form of a tree. Nowadays, applications generate massive amounts of XML data, which requires accurate and efficient query-able XML database systems. XML querying depends on XML labelling in much the same way as relational databases rely on indexes. Document order and structural information are encoded by labelling schemes, thus facilitating their use by queries without having to access the original XML document. Dynamic XML data, data which changes, complicates the labelling scheme. As demonstrated by much research efforts, it is difficult to allocate unique labels to nodes in a dynamic XML tree so that all structural relationships between the nodes are encoded by the labels. Static XML documents are generally managed with labelling schemes that use simple labels. By contrast, dynamic labelling schemes have extra labelling costs and lower query performance to allow random updates irrespective of the document update frequency. Given that static and dynamic XML documents are often not clearly distinguished, a labelling scheme whose efficiency does not depend on updating frequency would be useful. The GroupBased labelling scheme proposed in this thesis is compatible with static as well as dynamic XML documents. In particular, this scheme has a high performance in processing dynamic XML data updates. What differentiates it from other dynamic labelling schemes is its uniform behaviour irrespective of whether the document is static or dynamic, ability to determine all structural relationships between nodes, and the improved query performance in both types of document. The advantages of the GroupBased scheme in comparison to earlier schemes are highlighted by the experiment results

Compressing Labels of Dynamic XML Data using Base-9 Scheme and Fibonacci Encoding

The flexibility and self-describing nature of XML has made it the most common mark-up language used for data representation over the Web. XML data is naturally modelled as a tree, where the structural tree information can be encoded into labels via XML labelling scheme in order to permit answers to queries without the need to access original XML files. As the transmission of XML data over the Internet has become vibrant, it has also become necessary to have an XML labelling scheme that supports dynamic XML data. For a large-scale and frequently updated XML document, existing dynamic XML labelling schemes still suffer from high growth rates in terms of their label size, which can result in overflow problems and/or ambiguous data/query retrievals. This thesis considers the compression of XML labels. A novel XML labelling scheme, named “Base-9”, has been developed to generate labels that are as compact as possible and yet provide efficient support for queries to both static and dynamic XML data. A Fibonacci prefix-encoding method has been used for the first time to store Base-9’s XML labels in a compressed format, with the intention of minimising the storage space without degrading XML querying performance. The thesis also investigates the compression of XML labels using various existing prefix-encoding methods. This investigation has resulted in the proposal of a novel prefix-encoding method named “Elias-Fibonacci of order 3”, which has achieved the fastest encoding time of all prefix-encoding methods studied in this thesis, whereas Fibonacci encoding was found to require the minimum storage. Unlike current XML labelling schemes, the new Base-9 labelling scheme ensures the generation of short labels even after large, frequent, skewed insertions. The advantages of such short labels as those generated by the combination of applying the Base-9 scheme and the use of Fibonacci encoding in terms of storing, updating, retrieving and querying XML data are supported by the experimental results reported herein