Under several emerging application scenarios, such as in smart cities, operational
monitoring of large infrastructure, wearable assistance, and Internet of Things, continuous …

Data stream processing (DSP) has emerged over the years as the reference paradigm for
the analysis of continuous and fast information flows, which often have to be processed with …

As users of" big data" applications expect fresh results, we witness a new breed of stream
processing systems (SPS) that are designed to scale to large numbers of cloud-hosted …

Stream Processing (SP) has evolved as the leading paradigm to process and gain value
from the high volume of streaming data produced, eg, in the domain of the Internet of Things …

In the last few years a new research area, called stream reasoning, emerged to bridge the
gap between reasoning and stream processing. While current reasoning approaches are …

Stream processing is an emerging paradigm to handle data streams upon arrival, powering
latency-critical application such as fraud detection, algorithmic trading, and health …

The need for low latency analysis over high-velocity data streams motivates the need for
distributed continuous dataflow systems. Contemporary stream processing systems use …

Enabling a Smart City Application Ecosystem: Requirements and Architectural Aspects Page 1
Internet of Things, People, and Processes Editor: Schahram Dustdar • dustdar@dsg.tuwien.ac.at …

Future 5G systems will pave the way to a completely new societal paradigm where access to
information will be available anywhere, anytime, and to anyone or anything. Most of the …

Abstract Distributed Stream Processing Systems (DSPS) are “Fast Data” platforms that allow
streaming applications to be composed and executed with low latency on commodity …