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 …

Big data processing systems (eg, Hadoop, Spark, Storm) contain a vast number of
configuration parameters controlling parallelism, I/O behavior, memory settings, and …

The COVID-19 pandemic led universities to transform the traditional teaching methodologies
into distance education. Therefore, social media has become progressively prominent as …

We are currently living in the big data era, in which it has become more necessary than ever
to develop “smart” schedulers. It is common knowledge that the default Storm scheduler, as …

An important as well as challenging task in modern applications is the management and
processing with very short delays of large data volumes. It is quite often, that the capabilities …

Cloud environments have provided great help for the development of big data. Today, cloud
environments have become the most active platform for big data analysis applications …

In the current digital era, data is budding tremendously from various sources like banks,
businesses, education, entertainment, etc. Due to its significant consequence, it became a …

Purpose Creating a real-time data integration when developing an internet-of-things (IoT)-
based warehouse is still faced with challenges. It involves a diverse knowledge of novel …

Acoustic Emission (AE) and Guided Ultrasonic Waves (GUWs) are non-destructive testing
(NDT) methods in several industrial sectors for, eg, proof testing and periodic inspection of …

Nowadays, there is an accelerating need to efficiently and timely handle large amounts of
data that arrives continuously. Streams of big data led to the emergence of several …