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

Distributed data stream processing systems (DSPSs) such as Storm, Flink, and Spark
Streaming are now routinely used to process continuous data streams in (near) real-time …

We present Crowbar, a deductive verification tool for the Active Object language ABS.
Crowbar implements novel specification approaches specifically for distributed systems. For …

Serverless computing promises to significantly simplify cloud computing by providing
Functions-as-a-Service where invocations of functions, triggered by events, are …

Apache Spark is one of the most commonly used frameworks for Big Data processing.
Research on the provided streaming dynamic resource allocation feature, has been shown …

Streams of data are produced today at an unprecedented scale. Efficient and stable
processing of these streams requires a careful interplay between the parameters of the …

Nowadays, Spark Streaming, a computing framework based on Spark, is widely used to
process streaming data such as social media data, IoT sensor data or web logs. Due to the …

大数据流的高效存储与索引是当今数据领域的一大难点. 面向带有时间属性的数据流,
根据其时间属性, 将数据流划分为连续的时间窗口, 提出了基于双层B+ 树的分布式索引结构WB …

The servitization of business makes companies increasingly dependent on providing
carefully designed user experiences for their service offerings. User journeys model services …

The growing need to identify patterns in data and automate decisions based on them in near-
real time, has stimulated the development of new machine learning (ML) applications …