Serverless computing is growing in popularity by virtue of its lightweight and simplicity of
management. It achieves these merits by reducing the granularity of the computing unit to …

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

The next generation of AI applications will continuously interact with the environment and
learn from these interactions. These applications impose new and demanding systems …

Video cameras have been deployed at scale today. Driven by the breakthrough in deep
learning (DL), organizations that have deployed these cameras start to use DL-based …

In recent years, many applications have started using serverless computing platforms
primarily due to the ease of deployment and cost efficiency they offer. However, the existing …

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 …

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 …

The development of cloud computing delivery models inspires the emergence of cloud-
native computing. Cloud-native computing, as the most influential development principle for …

Many Internet of Things (IoT) applications would benefit if streams of data could be analyzed
rapidly at the Edge, near the data source. However, existing Stream Processing Engines …

Over the last decade, several interconnected disruptions have happened in the large scale
distributed and parallel computing landscape. The volume of data currently produced by …