An Evaluation of Data Stream Processing Systems for Data Driven Applications

Benchmarking Distributed Stream Data Processing Systems

The need for scalable and efficient stream analysis has led to the development of many open-source streaming data processing systems (SDPSs) with highly diverging capabilities and performance characteristics. While first initiatives try to compare the systems for simple workloads, there is a clear gap of detailed analyses of the systems’ performance characteristics. In this paper, we propose a ...

Dynamic Data Driven Applications Systems

This is the 5 International Workshop on Dynamic Data Driven Applications Systems (DDDAS), organized in conjunction with ICCS. The DDDAS concept entails the ability to dynamically incorporate data into an executing application simulation, and in reverse, the ability of applications to dynamically steer measurement processes. Such dynamic data inputs can be acquired in real-time on-line or they c...

Processing Moving Object Data Streams with Data Stream Management Systems

With the wide spread of cheap and mobile GPS sensors as well as mobile data connections, live streams from moving objects are becoming a huge data source. The services based on these data streams, for example, for connected cars, vessels or smartphone users, need real-time results for queries based on the current or even near-future positions of the moving objects. Spatio-temporal data from mov...

Design Tools for Dynamic, Data-Driven, Stream Mining Systems

Title of dissertation: DESIGN TOOLS FOR DYNAMIC, DATA-DRIVEN, STREAM MINING SYSTEMS Kishan Palintha Sudusinghe, Doctor of Philosophy, 2015 Dissertation directed by: Professor Shuvra S. Bhattacharyya Department of Electrical and Computer Engineering and Institute for Advanced Computer Studies The proliferation of sensing devices and costand energy-efficient embedded processors has contributed to...

Synchronizing data stream processing