Analytics provided on top of large scale data streams are the key research subject for future
decision making applications. The huge volumes of data make their partitioning imperative …

Current applications require the processing of huge amounts of data produced by
applications or end users personal devices. In such settings, intelligent analytics on top of …

The new era of the Internet of Things (IoT) reveals new potentials for the management of
numerous devices. Such devices produce data streams that are guided to the Cloud for …

Data management at the edge of the network can increase the performance of applications
as the processing is realized close to end users limiting the observed latency in the …

Abstract Systems for processing continuous monitoring queries over data streams must be
adaptive because data streams are often bursty and data characteristics may vary over time …

In large-scale, heterogeneous information systems, mediators are widely used for query
processing and the good operation of a system strongly depends on the way the mediator …

Performing complex analysis on top of massive data stores is essential to most modern
enterprises and organizations and requires simple, flexible and powerful syntactic constructs …

This article deals with continuous conjunctive queries with arithmetic comparisons and
optional aggregation over multiple data streams. An algorithm is presented for determining …

Data partitioning plays a critical role in data stream processing. Current data partitioning
techniques use simple, static heuristics that do not incorporate feedback about the quality of …

Recent years have witnessed an increasing interest in designing algorithms for querying
and analyzing streaming data (ie, data that is seen only once in a fixed order) with only …