Context Stream processing is a popular paradigm to continuously process huge amounts of
data. Runtime adaptation plays a significant role in supporting the optimization of data …

Many applications process high volumes of streaming data, among them Internet traffic
analysis, financial tickers, and transaction log mining. In general, a data stream is an …

Multiversion concurrency control (MVCC) and design principles thereof are ingrained in
modern database management systems, thus promoting remarkable progress in managing …

Stream applications gained significant popularity over the last years that lead to the
development of specialized stream engines. These systems are designed from scratch with …

Abstract Linked Stream Data has emerged as an effort to represent dynamic, time-
dependent data streams following the principles of Linked Data. Given the increasing …

The intrusion response component of an overall intrusion detection system is responsible for
issuing a suitable response to an anomalous request. We propose the notion of database …

Database management systems (DBMSs) have been used successfully in traditional
business applications that require persistent data storage and an efficient querying …

This paper addresses the challenges in detecting the potential correlation between
numerical data streams, which facilitates the research of data stream mining and pattern …

Explosive increase of real-time data sources, so-called" data streams"(or just" steams") and
increasing demands for real-time analysis over streams give rise to realtime analysis over …

Sensors, mobile devices and social platforms generate an immense amount of stream data
in various formats and schemata. For these areas, the idea of Linked Stream Data is to …