Expanding sensor networks to automate knowledge acquisition

The availability of accurate, low-cost sensors to scientists has resulted in widespread deployment in a variety of sporting and health environments. The sensor data output is often in a raw, proprietary or unstructured format. As a result, it is often difficult to query multiple sensors for complex properties or actions. In our research, we deploy a heterogeneous sensor network to detect the various biological and physiological properties in athletes during training activities. The goal for exercise physiologists is to quickly identify key intervals in exercise such as moments of stress or fatigue. This is not currently possible because of low level sensors and a lack of query language support. Thus, our motivation is to expand the sensor network with a contextual layer that enriches raw sensor data, so that it can be exploited by a high level query language. To achieve this, the domain expert specifies events in a tradiational event-condition-action format to deliver the required contextual enrichment

Complex Event Processing with XChangeEQ

The emergence of event-driven architectures, automation of business processes, drastic cost-reductions in sensor technology, and a growing need to monitor IT systems (as well as other systems) due to legal, contractual, or operational considerations lead to an increasing generation of events. This development is accompanied by a growing demand for managing and processing events in an automated and systematic way. Complex Event Processing (CEP) encompasses the (automatable) tasks involved in making sense of all events in a system by deriving higher-level knowledge from lower-level events while the events occur, i.e., in a timely, online fashion and permanently. At the core of CEP are queries which monitor streams of "simple" events for so-called complex events, that is, events or situations that manifest themselves in certain combinations of several events occurring (or not occurring) over time and that cannot be detected from looking only at single events. Querying events is fundamentally different from traditional querying and reasoning with database or Web data, since event queries are standing queries that are evaluated permanently over time against incoming streams of event data. In order to express complex events that are of interest to a particular application or user in a convenient, concise, cost-effective and maintainable manner, special purpose Event Query Languages (EQLs) are needed. This thesis investigates practical and theoretical issues related to querying complex events, covering the spectrum from language design over declarative semantics to operational semantics for incremental query evaluation. Its central topic is the development of the high-level event query language XChangeEQ. In contrast to previous data stream and event query languages, XChangeEQ's language design recognizes the four querying dimensions of data extractions, event composition, temporal relationships, and, for non-monotonic queries involving negation or aggregation, event accumulation. XChangeEQ deals with complex structured data in event messages, thus addressing the need to query events communicated in XML formats over the Web. It supports deductive rules as an abstraction and reasoning mechanism for events. To achieve a full coverage of the four querying dimensions, it builds upon a separation of concerns of the four querying dimensions, which makes it easy-to-use and highly expressive. A recurrent theme in the formal foundations of XChangeEQ is that, despite the fundamental differences between traditional database queries and event queries, many well-known results from databases and logic programming are, with some importance changes, applicable to event queries. Declarative semantics for XChangeEQ are given as a (Tarski-style) model theory with accompanying fixpoint theory. This approach accounts well for (1) data in events and (2) deductive rules defining new events from existing ones, two aspects often neglected in previous work of semantics of EQLs. For the evaluation of event queries, this work introduces operational semantics based on an extended and tailored form of relational algebra and query plans with materialization points. Materialization points account for storing and maintaining information about those received events that are relevant for, i.e., can contribute to, future query answers, as well as for an incremental evaluation that avoids recomputing certain intermediate results. Efficient state maintenance in incremental evaluation is approached by "differentiating" algebra expressions, i.e., by deriving expressions for computing only the changes to materialization points. Knowing how long an event is relevant is a prerequisite for performing garbage collection during event query evaluation and also of central importance for developing cost-based query planners. To this end, this thesis introduces a notion of relevance of events (to a given query plan) and develops methods for determining temporal relevance, a particularly useful form based on time-related information

A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes

Twelve Theses on Reactive Rules for the Web

Reactivity, the ability to detect and react to events, is an essential functionality in many information systems. In particular, Web systems such as online marketplaces, adaptive (e.g., recommender) systems, and Web services, react to events such as Web page updates or data posted to a server. This article investigates issues of relevance in designing high-level programming languages dedicated to reactivity on the Web. It presents twelve theses on features desirable for a language of reactive rules tuned to programming Web and Semantic Web applications

Reactivity on the Web

Reactivity, the ability to detect simple and composite events and respond in a timely manner, is an essential requirement in many present-day information systems. With the emergence of new, dynamic Web applications, reactivity on the Web is receiving increasing attention. Reactive Web-based systems need to detect and react not only to simple events but also to complex, real-life situations. This paper introduces XChange, a language for programming reactive behaviour on the Web, emphasising the querying of event data and detection of composite events

TypEx : a type based approach to XML stream querying

We consider the topic of query evaluation over semistructured information streams, and XML data streams in particular. Streaming evaluation methods are necessarily eventdriven, which is in tension with high-level query models; in general, the more expressive the query language, the harder it is to translate queries into an event-based implementation with finite resource bounds

Complex Event Processing (CEP)

Event-driven information systems demand a systematic and automatic processing of events. Complex Event Processing (CEP) encompasses methods, techniques, and tools for processing events while they occur, i.e., in a continuous and timely fashion. CEP derives valuable higher-level knowledge from lower-level events; this knowledge takes the form of so called complex events, that is, situations that can only be recognized as a combination of several events. 1 Application Areas Service Oriented Architecture (SOA), Event-Driven Architecture (EDA), cost-reductions in sensor technology and the monitoring of IT systems due to legal, contractual, or operational concerns have lead to a significantly increased generation of events in computer systems in recent years. This development is accompanied by a demand to manage and process these events in an automatic, systematic, and timely fashion. Important application areas for Complex Event Processing (CEP) are the following