Depending on energy sources and demand, the carbon intensity of the public power grid
fluctuates over time. Exploiting this variability is an important factor in reducing the emissions …

Stream processing pipelines need to handle workload fluctuations (eg, daily patterns,
popularity spikes) by scaling up/down the resources contributed to running jobs. While there …

To maintain a stable Quality of Service (QoS), these systems require a sufficient allocation of
resources. At the same time, over-provisioning can result in wasted energy and high …

The growing electricity demand of cloud and edge computing increases operational costs
and will soon have a considerable impact on the environment. A possible countermeasure is …

Distributed Stream Processing (DSP) focuses on the near real-time processing of large
streams of unbounded data. To increase processing capacities, DSP systems are able to …

A smart grid cyber physical system (SG-CPS) is an optimal fusion of a power network
infrastructure and cyber system based on a communicating network. The SG-CPS employs …

Stream processing has become a critical component in the architecture of modern
applications. With the exponential growth of data generation from sources such as the …

Computing, storage, and network resources are available as a utility today through the
methods of cloud computing. Users can provision the resources, platforms, and services …

In light of continuously growing amounts of data as well as the proliferation of machine
learning use cases, batch processing of data remains an important procedure. Batch …