Data Stream Processing (DSP) is a widely used programming paradigm to process an
unbounded event stream. Often, DSP frameworks are deployed on the cloud with a scalable …

The popularity and proliferation of the Internet of Things (IoT) paradigm is resulting in a
growing number of devices connected to the Internet. These devices are generating and …

The Internet of Things has enabled many application scenarios where a large number of
connected devices generate unbounded streams of data, often processed by data stream …

The recent spectacular rise of the Internet of Things and the associated augmentation of the
data deluge motivated the emergence of Edge computing as a means to distribute …

In stream processing, data is streamed as a continuous flow of data items, which are
generated from multiple sources and geographical locations. The common approach for …

Distributed Stream Processing Systems (DSPSs) are attracting increasing industrial and
academic interest as flexible tools to implement scalable and cost-effective on-line analytics …

Emerging trends like Big Data and the Internet of Things pose new challenges to
established data stream processing engines. Especially, with the advent of the Internet of …

Stream Processing Frameworks (SPF, eg, Apache Storm) are solutions that facilitate and
manage the execution of processing topologies that consist of multiple parallelizable steps …

The Internet of Things is getting more and more traction, nevertheless, state-of-the-art
approaches only focus on specific aspects, like the integration of heterogeneous devices or …

Stream processing applications handle unbounded and continuous flows of data items
which are generated from multiple geographically distributed sources. Two approaches are …