Bonsai: an event-based framework for processing and controlling data streams
نویسندگان
چکیده
منابع مشابه
Bonsai: an event-based framework for processing and controlling data streams
The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for t...
متن کاملData streams and event processing (DSEP)
The processing of continuous data sources has become an important paradigm of modern data processing and management, covering manya pplications and domains such as monitoring and controlling networks or complexproduction system as well complexevent processing in medicine, finance or compliance. The goal of the workshop is to attract both academic and industrial contributions to foster the excha...
متن کاملQueueLinker: A Framework for Parallel Distributed Processing of Data Streams
With the development of computer systems, many more devices are being connected to the network and generating ‘data stream.’ Analyzing data streams in real-time offers valuable information about human activities and contributes to many information services. QueueLinker enables programmers to build data stream processing applications by implementing application modules that use a producer–consum...
متن کاملActive Complex Event Processing over Event Streams
State-of-the-art Complex Event Processing technology (CEP),while effective for pattern query execution, is limited in itscapability of reacting to opportunities and risks detected bypattern queries. Especially reactions that affect the queryresults in turn have not been addressed in the literature.We propose to tackle these unsolved problems by embed-ding active rule sup...
متن کاملDynamic Low-Latency Distributed Event Processing of Sensor Data Streams
Event-based systems (EBS) are used to detect meaningful events with low latency in surveillance, sports, finances, etc. However, with rising data and event rates and with correlations among these events, processing can no longer be sequential but it needs to be distributed. However, naively distributing existing approaches not only cause failures as their order-less processing of events cannot ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Neuroinformatics
سال: 2015
ISSN: 1662-5196
DOI: 10.3389/fninf.2015.00007