Hypergraphs are a generalization of graphs where edges (aka nets) are allowed to connect
more than two vertices. They have a similarly wide range of applications as graphs. This …

Particle physics has an ambitious and broad experimental programme for the coming
decades. This programme requires large investments in detector hardware, either to build …

Large scale streaming systems aim to provide high throughput and low latency. They are
often used to run mission-critical applications, and must be available 24x7. Thus such …

Random graph models are frequently used as a controllable and versatile data source for
experimental campaigns in various research fields. Generating such data-sets at scale is a …

Stream-processing workloads and modern shared cluster environments exhibit high
variability and unpredictability. Combined with the large parameter space and the diverse …

Out-of-core systems rely on high-performance cache sub-systems to reduce the number of
I/O operations. Although the page cache in modern operating systems enables transparent …

Nowadays, we are witnessing the diffusion of Stream Processing Systems (SPSs) able to
analyze data streams in near realtime. Traditional SPSs like Storm and Flink target …

Data structures for efficient sampling from a set of weighted items are an important building
block of many applications. However, few parallel solutions are known. We close many of …

In container management systems, such as Kubernetes, the scheduler has to place
containers in physical machines and it should be aware of the degradation in performance …

Stream processing applications deal with millions of data items continuously generated over
time. Often, they must be processed in real-time and scale performance, which requires the …