The IBM Streams Processing Language (SPL) is the programming language for IBM
InfoSphere® Streams, a platform for analyzing Big Data in motion. By “Big Data in motion,” …

In this paper, we present the first comprehensive survey of window types for stream
processing systems which have been presented in research and commercial systems. We …

Rich mobile applications are characterized by rich functionality, offline usability and
portability. However, it isnot trivial to simultaneously satisfy all the three criteria. Existing …

Window aggregation is a core operation in data stream processing. Existing aggregation
techniques focus on reducing latency, eliminating redundant computations, or minimizing …

The Internet of Things is getting more and more traction, nevertheless, state-of-the-art
approaches only focus on specific aspects, like the integration of heterogeneous devices or …

Big data is revolutionizing how all sectors of our economy do business, including
telecommunication, transportation, medical, and finance. Big data comes in two flavors: data …

Analytical Stream Processing (ASP) and Complex Event Processing (CEP) extract
knowledge from unbounded data streams. ASP solutions are optimized for scalable cloud …

In our data-centric society, online services, decision making, and other aspects are
increasingly becoming heavily dependent on trends and patterns extracted from data. A …

This work presents an extensive case study on the model‐based design of a commercial‐
grade stream processing middleware (IBM's InfoSphere Streams) its runtime and language …

Data-stream management systems have for long been considered as a promising
architecture for fast data management. The stream processing paradigm poses an attractive …