Volker Linnemann

Embedding SPARQL into XQuery/XSLT

The tree-based languages XQuery and XSLT for XML are widely supported. Many tools do not yet support the new RDF graph query language SPARQL. We propose to embed SPARQL subqueries into XQuery/XSLT, such that XQuery and XSLT benefit from the graph query language constructs of SPARQL, and SPARQL benefits from features of XQuery/XSLT, which SPARQL does not support. The embedding enables XQuery/XSLT tools to handle at the same time XML queries and SPARQL subqueries, and XML and RDF data.

A SPARQL Engine for Streaming RDF Data

The basic data format of the semantic Web is RDF. SPARQL, which has been developed by the W3C, is the upcoming standard for RDF query languages. Typical engines for processing SPARQL queries on RDF data first read all RDF data, may build indices of the complete read data and afterwards evaluate SPARQL queries. Such engines cannot operate on streaming RDF data. Streaming query engines operating on streams of data can (a) discard irrelevant input as early as possible, and thus save processing costs and space costs, (b) build indices only on those parts of the data, which are needed for the evaluation of the query, and (c) determine partial results of a query as early as possible, and thus evaluate queries more efficiently. We propose such a streaming SPARQL engine, which is the first streaming SPARQL engine to the best of our knowledge.

Efficient processing of SPARQL joins in memory by dynamically restricting triple patterns

Since there are a lot of similar or common properties between RDF and relational databases and between SPARQL and SQL, many efforts focus on leveraging the research results of optimizing relational query languages for optimizing SPARQL queries. However, SPARQL has its own characteristics different from SQL, which are not fully exploited by existing work. Therefore, there is still much space for research on optimizing SPARQL queries. Based on the triple nature of RDF data, we create 7 indices to retrieve RDF data quickly; based on the SPARQL-specific properties and the 7 indices, we develop a new, efficient approach to computing join by dynamically restricting triple patterns. Our experimental results show the efficiency of our approach.

Translating XPath queries into SPARQL queries

The W3C has developed XPath [3] as a query language for XML data. XPath is embedded in many other languages like XQuery and XSLT. The name of XPath derives from its basic concept, the path expression, with which the user can hierarchically address the nodes of the XML data. The user of XPath may not only use simple relationships like parent-child, but also more complex relationships like the descendant relationship, which is the transitive closure of the parent-child relationship. Furthermore, complex filter expressions are allowed in XPath queries. RDF is a language for representing information about resources in the World Wide Web. SPARQL [2] supports querying RDF by triple and optional patterns, con- and disjunctions and extensible value testing.

LuposDate: a semantic web database system

Managing and querying Semantic Web are important issues for Semantic Web applications. Therefore, we have developed a Semantic Web database system with logically and physically optimized SPARQL engines to manage and query RDF data, named LuposDate. In order to present the functionalities of the LUPOSDATE system and engines, we have developed an online demonstration, which is available at http://www.ifis.uni-luebeck.de/index.php?id=luposdate-demo.

Efficient XML usage within wireless sensor networks

Integrating wireless sensor networks in heterogeneous networks is a complex task. A reason is the absence of a standardized data exchange format that is supported in all participating sub networks. XML has evolved to the de facto standard data exchange format between heterogeneous networks and systems. However, XML usage within sensor networks has not been introduced because of the limited hardware resources. In this paper, we introduce XML template objects making XML usage applicable within sensor networks. This new XML data binding technique provides significant high compression results while still allowing dynamic XML processing and XML navigation. This is a step towards more complex but exchangeable data management in sensor networks and the extension of the service-oriented paradigm to sensor network application engineering.

Hardware-accelerated join processing in large Semantic Web databases with FPGAs

The increasing amount of data to be processed by database systems asks for a continuous increase in processing power. While traditional system designs can hardly cope with these performance requirements, dedicated hardware accelerators provide the required processing power. However, dedicated hardware accelerators are inflexible and cannot be adapted to the requirements of a dedicated query. In this paper, a concept is introduced to improve the performance of a Semantic Web database by developing a flexible FPGA-based hardware accelerator. The feasibility of this approach is shown by implementing different types of join operators as one of the most important and most time consuming operators in query execution. The performance comparison between the proposed FPGA implementation and a software solution in C on a general-purpose processor shows a significant speed-up up to 10 times.

Accelerated join evaluation in Semantic Web databases by using FPGAs

While the amount of information steadily increases, the requirements on the response time to query these information become more strict. Under those conditions, conventional database systems reach their limits and cannot meet these performance requirements anymore. In recent years, systems with many processing cores are considered to satisfy these demands. Furthermore, these systems include more and more heterogeneous cores tailor‐made to solve one specific task in an efficient manner. However, dedicated hardware accelerators are inflexible and cannot be adapted to the requirements of a dedicated query. Thus, the challenge is orchestrating the diversity of the functionality of all the cores to be optimized for performance/energy efficiency. In this paper, a concept is introduced on how to develop a flexible Field‐Programmable Gate Arrays (FPGA)‐based hardware accelerator to improve the performance of query evaluation in a Semantic Web database. As a first step to the hardware/software system, several joint algorithms are implemented on an FPGA and evaluated against a well‐developed software solution (implemented in C). The comparison shows a significant speedup of up to 10 times. Because of the complexity of the join operator, it is promising that the overall performance of query evaluation can be further enhanced by processing whole queries on an FPGA. Copyright

Bringing the XML and Semantic Web Worlds Closer: Transforming XML into RDF and Embedding XPath into SPARQL

XPath is an established query language developed by the W3C for XML, which is supported by many tools and used in many applications. SPARQL is a new query language developed by the W3C for RDF data. Recently available SPARQL query evaluators do not deal with XML data and XPath queries. In this contribution, we show how to enable SPARQL query evaluators to deal with XML data and XPath queries in order to support XPath processing and SPARQL processing in parallel.

Redundancy Infrastructure for Service-Oriented Wireless Sensor Networks

Transfering the paradigm of service-oriented architecture (SOA) to sensor networks became an important research area in the last years. Amongst others, a couple of approaches deal with the flexible and robust service discovery and usage of services which takes the unsteady nature of WSNs into account. However, the approaches do not consider the case that services may get unavailable during their activity phase because of node failures. In this case, already collected or computed data will get lost and the service request of the service consumer remains unanswered. In this paper, we propose a redundancy infrastructure for service-oriented WSNs which deals with this special problem. The framework consists of an adaptive data replication technique and a service recovery solution. Whereas the replication technique ensures the survival beyond node failures, the recovery protocol restarts a failed service using the replicated data and enables the service to continue its functionality.