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 …

A recurrent challenge in real‐world applications is autonomous management of the
executions at run‐time. In this vein, stream processing is a class of applications that compute …

Big data attracts researchers and practitioners around the globe in their desire to effectively
manage the data deluge resulting from the ongoing evolution of the information systems …

Sensory data profoundly influences the quality of detected events in a distributed complex
event processing system (DCEP). Since each sensor's status is unstable at runtime, a single …

Systematic literature reviews (SLRs) are a central part of evidence-based research, which
involves collecting and integrating empirical evidence on specific research questions. A key …

Purpose As the global freight transport network has experienced high vulnerability and
threats from both natural and man-made disasters, as a result, a huge amount of data is …

The emergence of edge stream processing has created a new way of processing real-time
data from the Internet of Things (IoT), which comprises a plethora of geographically …

This paper investigates how to complement Complex Event Processing (CEP) with dynamic
quality monitoring mechanisms and support the dynamic integration of suitable sensory data …

With the proliferation of Internet of Things (IoT) devices, real-time stream processing at the
edge of the network has gained significant attention. However, edge stream processing …

IoT stream processing is an emerging technology that plays a crucial role in enabling time-
critical IoT applications, which often demand high accuracy and low latency. For example …