XML Streams Research Articles

A Novel encrypted XML streaming technique for indexing data on multiple channels

A Novel encrypted XML streaming technique for indexing data on multiple channels

XML Query Optimization for Improvement of Data Warehouses Information Processing

XML data warehouses give decision-support systems a chance to use complicated data by giving them a place to start. But native-XML database management systems are slow right now, so it is important to look into ways to make them faster. This study presents two strategies to think about. To start, we suggest using a link index that was made with the fact that XML warehouses have a lot of dimensions in mind. The join procedures are taken out, but the data from the first warehouse stays the same. Second, we show how to choose XML materialized views by grouping the query load to show how this can be done. To prove that these ideas work, we built a set of decision support XQuery tools and ran them against an XML data warehouse. We compared the results obtained with and without our optimization methods. Our tests show that it works, even though the queries themselves are a little hard to understand and the datasets themselves are very big. XML has emerged as the widely accepted standard for transmitting data over mobile wireless networks. In these kinds of networks, mobile clients can use a wireless broadcast channel to send queries to get the XML data they need. Because mobile devices are so small and have so little storage space and a short battery life, it may be hard for customers to download the whole XML data set on one of these devices. To solve this problem, you need to index XML data so that mobile clients only have to download the parts of the file they need. Users who want to access only certain parts of the XML content in an XML stream could use one of several indexing methods. Still, the indexing methods that are used now add more data to an XML stream that is already very large. This research comes up with a new XML stream structure for broadcasting XML data by compressing and summarizing the information about how XML nodes are put together. This study was conducted in the United Kingdom. When data is summed up before being sent, the time it takes to get it in XML format over a wireless broadcast channel can be cut down. The recommended XML stream structure also has indexes that will help you skip over any data that is not important. So, it could make it less likely that XML query results will drain the batteries of mobile devices when they are being processed. We also found that our suggested XML stream design was better than its predecessors in terms of access and tuning times for processing XML queries over the XML data stream. So, our architecture can be used to answer a wide range of XML questions.

Regular matching and inclusion on compressed tree patterns with constrained context variables

We study the complexity of regular matching and inclusion for compressed tree patterns with context variables subject to regular constraints. Context variables with regular constraints permit to properly generalize on unranked tree patterns with hedge variables. Regular inclusion on unranked tree patterns is relevant to certain query answering on Xml streams with references. We show that regular matching and inclusion with regular constraints can be reduced in polynomial time to the corresponding problem without regular constraints.

Query processing optimization in broadcasting XML data in mobile communications

Todays, XML as a de facto standard is used to broadcast data over mobile wireless networks. In these networks, mobile clients send their XML queries over a wireless broadcast channel and recieve their desired XML data from the channel. However, downloading the whole XML data by a mobile device is a challenge since the mobile devices used by clients are small battery powered devices with limited resources. To meet this challenge, the XML data should be indexed in such a way that the desired XML data can be found easily and only such data can be downloaded instead of the whole XML data by the mobile clients. Several indexing methods are proposed to selectively access the XML data over an XML stream. However, the existing indexing methods cause an increase in the size of XML stream by including some extra information over the XML stream. In this paper, a new XML stream structure is proposed to disseminate the XML data over a broadcast channel by grouping and summarizing the structural information of XML nodes. By summarizing such information, the size of XML stream can be reduced and therefore, the latency of retrieving the desired XML data over a wirless broadcast channel can be reduced. The proposed XML stream structure also contains indexes in order to skip from the irrelevant parts over the XML stream. It therefore can reduce the energy consumption of mobile devices in downloading the results of XML queries. In addition, our proposed XML stream structure can process different types of XML queries and experimental results showed that it improves the performace of XML query processing over the XML data stream compared to the existing research works in terms of access and tuning times.

A model for aggregation and filtering on encrypted XML streams in fog computing

The Internet of Things provides visions of innovative services and domain-specific applications. With the development of Internet of Things services, various structural data need to be transferred ...

An XML Streaming Data Processing Method based on Forest Transducer

An XML Streaming Data Processing Method based on Forest Transducer

A new structure and access mechanism for secure and efficient XML data broadcast in mobile wireless networks

A new structure for streaming the XML data is proposed which guarantees confidentiality of the XML data over the wireless stream.An access mechanism is proposed to efficiently process XML queries over the encrypted XML stream. Recently, the use of XML for data broadcasting in mobile wireless networks has gained many attentions. One of the most essential requirements for such networks is data confidentiality. In order to secure XML data broadcast in mobile wireless networks, mobile clients should obey a set of access authorizations specified on the original XML document. In such environments, mobile clients can only access authorized parts of encrypted XML stream based on their access authorizations. Several indexing methods have been proposed in order to have selective access to XML data over the XML stream. However, these indexing methods cannot be used for encrypted XML data. In this paper, we define a new structure for XML stream which supports data confidentiality of XML data over the wireless broadcast channel. We also define an access mechanism for our proposed structure to efficiently process XML queries over the encrypted XML stream. The experimental results demonstrate that the use of our proposed structure and access mechanism for XML data broadcast efficiently disseminates XML data in mobile wireless networks.

Multi-query processing of XML data streams on multicore

The multicore architecture has been the norm for all computing systems in recent years as it provides the CPU-level support of parallelism. However, existing algorithms for processing XML streams do not fully take advantage of the facility since they have not been devised to run in parallel. In this article, we propose several methods to parallelize the finite state automata (FSA)-based XML stream processing technique efficiently. We transform a large collection of XPath expressions into multiple FSA-based query indexes and then process XML streams in parallel by virtue of the index-level parallelism. Each core works only with its own query index so that no synchronization issue occurs while filtering XML streams with multiple path patterns given by users. We also present an in-memory MapReduce model that enables to process a large collection of twig pattern joins over XML streams simultaneously. Twig pattern joins in our approach are performed by multiple H/W threads in a shared and balanced way. Extensive experiments show that our algorithm outperforms conventional algorithms with an 8-core CPU by up to ten times for processing 10 million XPath expressions over XML streams.

Query XML Streaming Data with List

Query XML Streaming Data with List

LCA-based algorithms for efficiently processing multiple keyword queries over XML streams

In a stream environment, differently from traditional databases, data arrive continuously, unindexed and potentially unbounded, whereas queries must be evaluated for producing results on the fly. In this article, we propose two new algorithms (called SLCAStream and ELCAStream) for processing multiple keyword queries over XML streams. Both algorithms process keyword-based queries that require minimal or no schema knowledge to be formulated, follow the lowest common ancestor (LCA) semantics, and provide optimized methods to improve the overall performance. Moreover, SLCAStream, which implements the smallest LCA (SLCA) semantics, outperforms the state-of-the-art, with up to 49% reduction in response time and 36% in memory usage. In turn, ELCAStream is the first to explore the exclusive LCA (ELCA) semantics over XML streams.A comprehensive set of experiments evaluates several aspects related to performance and scalability of both algorithms, which shows they are effective alternatives to search services over XML streams.

面向XML流数据的树模式匹配方法

面向互联网时代XML流数据处理的高性能处理需求，充分考虑流数据查询需要处理持续到来的数据等特点，针对多数现有研究局限于XPath查询的缺陷，研究并实现了XML查询核心操作——树模式查询的流数据处理算法，通过实验说明该算法达到了XML流数据处理的性能要求。 For the needs of high-performance processing on XML stream data in the internet age, this paper fully considers that streaming data query needs to process the continuous arrival of data, etc., for the majority of the existing studies have been limited to XPath query defects, this paper studies and implements XML Query core operation—stream data processing algorithm on tree pattern matching through experiments show that the algorithm achieves the performance demand of XML stream data processing.

Path-based keyword search over XML streams

Purpose – In purpose of this paper is to propose a novel scheme to process XPath-based keyword search over Extensible Markup Language (XML) streams, where one can specify query keywords and XPath-based filtering conditions at the same time. Experimental results prove that our proposed scheme can efficiently and practically process XPath-based keyword search over XML streams. Design/methodology/approach – To allow XPath-based keyword search over XML streams, it was attempted to integrate YFilter (Diao et al., 2003) with CKStream (Hummel et al., 2011). More precisely, the nondeterministic finite automation (NFA) of YFilter is extended so that keyword matching at text nodes is supported. Next, the stack data structure is modified by integrating set of NFA states in YFilter with bitmaps generated from set of keyword queries in CKStream. Findings – Extensive experiments were conducted using both synthetic and real data set to show the effectiveness of the proposed method. The experimental results showed that the accuracy of the proposed method was better than the baseline method (CKStream), while it consumed less memory. Moreover, the proposed scheme showed good scalability with respect to the number of queries. Originality/value – Due to the rapid diffusion of XML streams, the demand for querying such information is also growing. In such a situation, the ability to query by combining XPath and keyword search is important, because it is easy to use, but powerful means to query XML streams. However, none of existing works has addressed this issue. This work is to cope with this problem by combining an existing XPath-based YFilter and a keyword-search-based CKStream for XML streams to enable XPath-based keyword search.

Early nested word automata for XPath query answering on XML streams

Algorithms for answering XPath queries on Xml streams have been studied intensively in the last decade. Nevertheless, there still exists no solution with high efficiency and large coverage. In this paper, we introduce early nested word automata in order to approximate earliest query answering algorithms for nested word automata. Our early query answering algorithm is based on stack-and-state sharing for running early nested word automata on all answer candidates with on-the-fly determinization. We prove tight upper complexity bounds on time and space consumption. We have implemented our algorithm in the QuiXPath system and show that it outperforms all previous tools in coverage on the XPathMark benchmark, while obtaining very high time and space efficiency and scaling to huge Xml streams. Furthermore, it turns out that our early query answering algorithm is earliest in practice on most queries from the XPathMark benchmark.11Thanks to the QuiXProc project of Inria and Innovimax and the CnrsSosp project.

Association rule extraction from XML stream data for wireless sensor networks.

With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy.

A study on parallelizing XML path filtering using accelerators

Publish-subscribe systems present the state of the art in information dissemination to multiple users. Such systems have evolved from simple topic-based to the current XML-based systems. XML-based pub-sub systems provide users with more flexibility by allowing the formulation of complex queries on the content as well as the structure of the streaming messages. Messages that match a given user query are forwarded to the user. This article examines how to exploit the parallelism found in XPath filtering. Using an incoming XML stream, parsing and matching thousands of user profiles are performed simultaneously by matching engines. We show the benefits and trade-offs of mapping the proposed filtering approach onto FPGAs, processing streams of XML at wire speed, and GPUs, providing the flexibility of software. This is in contrast to conventional approaches bound by the sequential aspect of software computing, associated with a large memory footprint. By converting XPath expressions into custom stacks, our solution is the first to provide support for complex XPath structural constructs, such as parent-child and ancestor descendant relations, whilst allowing wildcarding and recursion. The measured speedups resulting from the GPU and FPGA accelerations versus single-core CPUs are up to 6.6X and 2.5 orders of magnitude, respectively. The FPGA approaches are up to 31X faster than software running on 12 CPU cores.

A Standard-based Model for the Exchange of 3D Geological Data

A wide range of methodologies and software applications have been developed to generate 3-Dimensional (3D) geological model data. One of the main open issues is the exchange of these heterogeneous data from different sources, which influences the sharing and integration of 3D geodata. It is also a necessity to take into consideration the semantics of 3D geological data to enable its full exchange. A standard based geologic data model (sGDM) is proposed to offer an xml-based data exchange of 3D geological models. sGDM totally reuses the standard of GeoSciML declared by the International Union of Geological Sciences (IUGS) as the core module for defining geological feature objects. Then geological features can be integrated into a geological model within a top-to-down architecture of geological model – feature group – geological feature. The Symbology Encoding (SE) standard from Open Geospatial Consortium (OGC) is utilized and extended by sGDM to define 3D visualization parameters of geological features. Besides, sGDM has benefited from several other existing standards, such as X3D proposed by Web 3D Consortium, WMS, SLD, CityGML etc. that proposed by OGC. To evaluate the sGDM, we also presented a high level prototype architecture for the integrated, xml-based storage and management of 3D geological data. In this architecture, data user and provider can exchange information through a communication method using sGDM-defined xml streams.

High-performance complex event processing over hierarchical data

While Complex Event Processing (CEP) constitutes a considerable portion of the so-called Big Data analytics, current CEP systems can only process data having a simple structure, and are otherwise limited in their ability to efficiently support complex continuous queries on structured or semistructured information. However, XML-like streams represent a very popular form of data exchange, comprising large portions of social network and RSS feeds, financial feeds, configuration files, and similar applications requiring advanced CEP queries. In this article, we present the XSeq language and system that support CEP on XML streams, via an extension of XPath that is both powerful and amenable to an efficient implementation. Specifically, the XSeq language extends XPath with natural operators to express sequential and Kleene-* patterns over XML streams, while remaining highly amenable to efficient execution. In fact, XSeq is designed to take full advantage of the recently proposed Visibly Pushdown Automata (VPA), where higher expressive power can be achieved without compromising the computationally attractive properties of finite state automata. Besides the efficiency and expressivity benefits, the choice of VPA as the underlying model also enables XSeq to go beyond XML streams and be easily applicable to any data with both sequential and hierarchical structures, including JSON messages, RNA sequences, and software traces. Therefore, we illustrate the XSeq's power for CEP applications through examples from different domains and provide formal results on its expressiveness and complexity. Finally, we present several optimization techniques for XSeq queries. Our extensive experiments indicate that XSeq brings outstanding performance to CEP applications: two orders of magnitude improvement is obtained over the same queries executed in general-purpose XML engines.

실패 전이를 갖는 트리를 이용한 스트리밍 XML 하드웨어 파서

Web-services employ an XML to represent data and an XML parser is needed to use data. The DOM(Document Object Model) is widely used to parse an XML, but it is not suitable for any systems with limited resources because it requires a preprocessing to create the DOM and additional memory space. In this paper, we propose the StreXTree(Streaming XML Tree) with failure transitions and without any preprocessing tasks in order to improve the system performance. Compared to other works, our StreXTree parser achieves 2.39x and 3.02x improvement in system performance in Search and RBStreX, respectively. In addition, our StreXTree parser supports Well-Formed checking to verify the syntax and structure of XML.

PS+Pre/Post: A novel structure and access mechanism for wireless XML stream supporting twig pattern queries

XML data broadcast is an efficient way to disseminate XML data to a large number of mobile clients in mobile wireless networks. Recently, several indexing methods have been proposed to improve the performance of XML query processing in terms of access time and tuning time over XML streams. However, existing indexing methods cannot process twig pattern XML queries. In this paper, we propose a novel structure for streaming XML data called PS+Pre/Post by integrating the path summary technique and the pre/post labeling scheme. Our proposed XML stream structure exploits the benefits of the path summary technique and the pre/post labeling scheme to efficiently process different types of XML queries over the broadcast stream. Experimental results show that our proposed XML stream structure improves the performance of access time and tuning time in processing different types of XML queries.

An energy conservation indexing method for secure XML data broadcast in mobile wireless networks

Secure broadcasting of XML data is becoming an essential requirement for many applications in mobile wireless networks. Several indexing methods have been proposed to reduce the tuning time in processing the XML queries over the wireless XML stream. Tuning time is the sum of period of times which a mobile client stays in active mode in order to retrieve the required data over the wireless stream. Therefore, it is frequently used to estimate the energy consumption of a mobile client. The problem of existing indexing methods is that they cannot directly be applied to an encrypted XML stream since mobile clients can only access the authorized parts of the XML data in an encrypted XML stream. In this paper, we define a unit structure of an XML stream called SecNode which guarantees confidentiality of the XML data in the wireless stream. We also define two indexes called Min (NCS) and Min (NIS) for the SecNode structure based on the set of access authorizations specified in the original XML document in order to efficiently process the XML queries over the encrypted XML stream. Experimental results show that the use of the SecNode structure for secure XML data broadcast improves the performance of XML query processing in terms of tuning time and therefore reduces the power consumption at mobile clients.