The growing amount of data in healthcare industry has made inevitable the adoption of big
data techniques in order to improve the quality of healthcare delivery. Despite the integration …

The concept of event processing is established as a generic computational paradigm in
various application fields. Events report on state changes of a system and its environment …

Stream processing has been an active research field for more than 20 years, but it is now
witnessing its prime time due to recent successful efforts by the research community and …

Complex event processing (CEP) systems that evaluate queries over streams of events may
face unpredictable input rates and query selectivities. During short peak times, exhaustive …

Elastic data stream processing enables applications to query and analyze streams of real
time data. This is commonly facilitated by processing the flow of the data streams using a …

For machine manufacturing companies, besides the production of high quality and reliable
machines, requirements have emerged to maintain machine-related aspects through digital …

Real-time analytics is a relatively new branch of analytics. A common definition of real-time
analytics is that it consists in analyzing data as quickly as possible over the most recent data …

The ubiquity of data streams in different fields of computing has led to the emergence of
Stream Processing Systems (SPSs) used to program applications that extract insights from …

The checkpoint roll-backward methodology is the underlying technology of several fault-
tolerance solutions for continuous stream processing systems today, implemented either …

High level reasoning is becoming essential to autonomous systems such as robots. Both the
information available to and the reasoning required for such autonomous systems is …