This paper focuses on facilitating state-of-the-art applications of big data analytics (BDA)
architectures and infrastructures to telecommunications (telecom) industrial sector. Telecom …

Distributed computing frameworks are the fundamental component of distributed computing
systems. They provide an essential way to support the efficient processing of big data on …

With the rapid evolution of the Internet, Internet of Things (IoT), and geographic information
systems (GIS), spatio-temporal Big Data (STBD) is experiencing exponential growth …

Buku" Teknologi Big Data: Pengantar dan Penerapan di Berbagai Bidang" merangkum
esensi teknologi Big Data dari awal hingga penerapannya dalam konteks kehidupan nyata …

Stream processing has inspired new computational approaches to facilitate effectiveness
and efficiency. One such approach is the dynamic pipeline, which serves as a powerful …

We introduce a novel logic-based system for reasoning over data streams, which relies on a
framework enabling a tight, fine-tuned interaction between Apache Flink and the-DLV …

The availability of geodata with high spatial and temporal resolution is increasing steadily.
Often, these data are continuously generated by distributed sensor networks and provided …

On computing clusters, the autoscaler is responsible for allocating resources for jobs or
finegrained tasks to ensure their Quality of Service. Due to a more precise resource …

Apache Flink is an open-source, soft real-time stream processing framework underlying
many modern systems dealing with cloud and real-time computing, data analytics, and the …

Flink is regarded as a promising distributed data processing engine for unifying bounded
data and unbounded data. Unbalanced workloads upon multiple workers/task …