A large number of distributed applications requires continuous and timely processing of
information as it flows from the periphery to the center of the system. Examples include …

One of the major applications of future generation parallel and distributed systems is in big-
data analytics. Data repositories for such applications currently exceed exabytes and are …

Abstract Many Big Data technologies were built to enable the processing of human
generated data, setting aside the enormous amount of data generated from Machine-to …

Data stream management systems may be subject to higher input rates than their resources
can handle. When overloaded, the system must shed load in order to maintain low-latency …

In recent years, a new class of applications has come to the forefront {p-marily due to the
advancement in our ability to collect data from multitudes of devices, and process them e …

Temporal data analysis in data warehouses and datastreaming systems often uses time
decay to reduce the importance of older tuples, without eliminating their influence, on the …

Discrete event simulation (DES) application is not as widely perceived as being useful for
problem solving in the health‐care arena as in other application areas. Suggests that this …

Several complex event processing (CEP) middleware solutions have been proposed in the
past. They act by processing primitive events generated by sources, extracting new …

Event correlation has become the cornerstone of many reactive applications, particularly in
distributed systems. However, support for programming with complex events is still rather …

The past decade has seen rapid growth of distributed stream data processing systems.
Under these systems, a stream application is realized as a Directed Acyclic Graph (DAG) of …