We introduce BOURBON, a log-structured merge (LSM) tree that utilizes machine learning to
provide fast lookups. We base the design and implementation of BOURBON on empirically …

Time series are widely used to record information in applications developed with Internet of
Things (IoT) devices, where sensors are used to collect large amounts of data. These …

Data streaming enables online monitoring of large and continuous event streams in Cyber-
Physical Systems (CPSs). In such scenarios, fine-grained backward provenance tools can …

The rapid growth of Internet of Things (IoT) and sensing technologies has led to an
increasing interest in time-series data analysis. In many domains, detecting patterns of IoT …

Approximating series of timestamped data points using a sequence of line segments with a
maximum error guarantee is a fundamental data compression problem, termed as piecewise …

Applications for adaptive (sometimes also called smart) Cyber-Physical Systems are
blossoming thanks to the large volumes of data, sensed in a continuous fashion, in large …

Streaming computing attracts intense attention because of the demand for massive data
analyzing in real-time. Due to unbounded and continuous input, the volume of streaming …

Data are naturally collected in their raw state and must undergo a series of preprocessing
steps to obtain data in their input state for Artificial Intelligence (AI) and other applications …

The growing interest in data analysis applications for Cyber–Physical Systems stems from
the large amounts of data such large distributed systems sense in a continuous fashion. A …

Purpose Minimizing the energy consumption in a wireless sensor node is important for
lengthening the lifetime of a battery. Radio transmission is the most energy-consuming task …