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15
Poster: Towards an Inexact Semantic Complex Event Processing Framework
"... Complex event processing (CEP) deals with detecting realtime situations, represented as event patterns, from among an event cloud. The state-of-the-art CEP systems process events as plain data tuples and are limited to detect precisely defined patterns. Emerging application areas like optimization i ..."
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Complex event processing (CEP) deals with detecting realtime situations, represented as event patterns, from among an event cloud. The state-of-the-art CEP systems process events as plain data tuples and are limited to detect precisely defined patterns. Emerging application areas like optimization in smart power grids require CEP to incorporate semantic knowledge of the domain for easier pattern specification, and detect inexact patterns in the presence of uncertainties. In this paper, we present motivating use cases, discuss limitations of existing CEP systems and describe our
From Regular Expressions to Nested Words: Unifying Languages and Query Execution for Relational and XML Sequences
, 2010
"... There is growing interest in query language extensions for pattern matching over event streams and stored database sequences, due to the many important applications that such extensions make possible. The push for such extensions has led DBMS vendors and DSMS venture companies to propose Kleene-clos ..."
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There is growing interest in query language extensions for pattern matching over event streams and stored database sequences, due to the many important applications that such extensions make possible. The push for such extensions has led DBMS vendors and DSMS venture companies to propose Kleene-closure extensions of SQL standards, building on seminal research that demonstrated the effectiveness and amenability to efficient implementation of such constructs. These extensions, however powerful, suffer from limitations that severely impair their effectiveness in many real-world applications. To overcome these problems, we have designed the K*SQL language and system, based on our investigation of the nested words, which are recent models that generalize both words and trees. K*SQL extends the existing relational sequence languages, and also enables applications from other domains such as genomics, software analysis, and XML processing. At the same time, K*SQL remains extremely efficient, using our powerful optimizations for pattern search over nested words. Furthermore, we show that other sequence languages and XPath can be automatically translated into K*SQL, allowing for K*SQL to be also used as a high-performance query execution back-end for those languages. Therefore, K*SQL is a unifying SQL-based engine for sequence and XML queries, which provides novel optimization techniques for both.
Incorporating semantic knowledge into dynamic data processing for smart power grids
- In International Semantic Web Conference
, 2012
"... Abstract. Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require contin-uous information monitoring and integration present novel opportunities and challenges for S ..."
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Abstract. Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require contin-uous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promis-ing to model diverse Smart Grid domain knowledge for enhanced situa-tion awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic anal-ysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by di-verse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.
Pattern Matching over Sequences of Rows in a Relational Database System
, 2008
"... In Complex Event Processing (CEP) applications such as supply chain management and financial data analysis, the capability to match patterns over data sequences is increasingly becoming an important need. This not only involves finding event patterns of interest on live data streams but also require ..."
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In Complex Event Processing (CEP) applications such as supply chain management and financial data analysis, the capability to match patterns over data sequences is increasingly becoming an important need. This not only involves finding event patterns of interest on live data streams but also requires a similar functionality over archived sequences of streams for historical analysis, verification, and correlation. The goal of this thesis is to extend a relational database system with the capability to match patterns over contiguous sequences of rows stored in a database table. More specif-ically, we have implemented a major subset of the 2007 ANSI standard proposal on adding MATCH RECOGNIZE clause to standard SQL on top of the MySQL open-source database engine. We have done this in a way to leverage the existing MySQL architecture and process-ing model as much as possible, while at the same time carefully identifying the parts where brand new extensions were necessary. Thus, one of the main contributions of this thesis is that it clearly shows what it takes in general to add pattern matching capability to any relational
Optimization of Massive Pattern Queries by Dynamic Configuration Morphing
"... Abstract—Complex pattern queries play a critical role in many applications that must efficiently search databases and data streams. Current techniques support the search for multiple patterns using deterministic or non-deterministic automata. In practice however, the static pattern representation do ..."
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Abstract—Complex pattern queries play a critical role in many applications that must efficiently search databases and data streams. Current techniques support the search for multiple patterns using deterministic or non-deterministic automata. In practice however, the static pattern representation does not fully utilize available system resources, subsequently suffering from poor performance. Therefore a low overhead auto-reconfigurable automaton is needed that optimizes pattern matching performance. In this paper, we propose a dynamic system that entails the efficient and reliable evaluation of a very large number of pattern queries on a resource constrained system under changing stress-load. Our system prototype, Morpheus, pre-computes several query pattern representations, named templates, which are then morphed into a required form during run-time. Morpheus uses templates to speed up dynamic automaton reconfiguration. Results from empirical studies confirm the benefits of our approach, with three orders of magnitude improvement achieved in the overall pattern matching performance with the help of dynamic reconfiguration. This is accomplished only with a modest increase in amortized memory usage. I.
On Load Shedding in Complex Event Processing
"... Complex Event Processing (CEP) is a stream processing model that focuses on detecting event patterns in continuous event streams. While the CEP model has gained popularity in the research com-munities and commercial technologies, the problem of gracefully degrading performance under heavy load in th ..."
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Complex Event Processing (CEP) is a stream processing model that focuses on detecting event patterns in continuous event streams. While the CEP model has gained popularity in the research com-munities and commercial technologies, the problem of gracefully degrading performance under heavy load in the presence of re-source constraints, or load shedding, has been largely overlooked. CEP is similar to “classical ” stream data management, but addresses a substantially different class of queries. This unfortunately renders the load shedding algorithms developed for stream data process-ing inapplicable. In this paper we study CEP load shedding under various resource constraints. We formalize broad classes of CEP load-shedding scenarios as different optimization problems. We demonstrate an array of complexity results that reveal the hardness of these problems and construct shedding algorithms with perfor-mance guarantees. Our results shed some light on the difficulty of developing load-shedding algorithms that maximize utility.
Eviction Strategies for Semantic Flow Processing ⋆
"... Abstract. In order to cope with the ever-increasing data volume continuous processing of incoming data via Semantic Flow Processing systems have been proposed. These systems allow to answer queries on streams of RDF triples. To achieve this goal they match (triple) patterns against the incoming stre ..."
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Abstract. In order to cope with the ever-increasing data volume continuous processing of incoming data via Semantic Flow Processing systems have been proposed. These systems allow to answer queries on streams of RDF triples. To achieve this goal they match (triple) patterns against the incoming stream and generate/update variable bindings. Yet, given the continuous nature of the stream the number of bindings can explode and exceed memory; in particular when computing aggregates. To make the information processing practical Semantic Flow Processing systems, therefore, typically limit the considered data to a (moving) window. Whilst this technique is simple it may not be able to find patterns spread further than the window or may still cause memory overruns when data is highly bursty. In this paper we propose to maintain bindings (and thus memory) not on recency (i.e., a window) but on the likelihood of contributing to a complete match. We propose to base the decision on the matching likelihood and not creation time (fifo) or at random. Furthermore we propose to drop variable bindings instead of data as do load shedding approaches. Specifically, we systematically investigate deterministic and the matching-likelihood based probabilistic eviction strategy for dropping variable bindings in terms of recall. We find that a matching likelihood based eviction can outperform fifo and random eviction strategies on synthetic as well as real world data.
a Knowledge-Based Network
"... I, the undersigned, declare that the work described in this dissertation is, except where otherwise stated, entirely my own work and has not been submitted as an exercise for a degree at this or any other university. ..."
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I, the undersigned, declare that the work described in this dissertation is, except where otherwise stated, entirely my own work and has not been submitted as an exercise for a degree at this or any other university.
Contents
, 2007
"... 2.1 Visualization layer- event processing layer............. 3 2.2 Event processing layer- data acquisition layer........... 4 ..."
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2.1 Visualization layer- event processing layer............. 3 2.2 Event processing layer- data acquisition layer........... 4
Betreuer:
, 2008
"... Hiermit versichere ich, dass ich diese Diplomarbeit selbständig verfasst habe. Ich habe dazu keine anderen als die angegebenen Quellen und Hilfsmittel verwendet. ..."
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Hiermit versichere ich, dass ich diese Diplomarbeit selbständig verfasst habe. Ich habe dazu keine anderen als die angegebenen Quellen und Hilfsmittel verwendet.
