A big data acquisition engine based on rule engine

doi:10.1016/S1005-8885(13)60250-2

The Journal of China Universities of Posts and Telecommunications

Volume 20, Supplement 1, August 2013, Pages 45-49

https://doi.org/10.1016/S1005-8885(13)60250-2 Get rights and content

Abstract

Supervisory control and data acquisition (SCADA) systems based on Ethernet progress is open and modularization. This article aims to building a general data acquisition engine which combines rule engine and finite state automaton together. The combination describes big data acquisition flow and its rules in a flexible way, and helps to verify the security and correctness of the big data acquisition flow.

References (8)

HF Xu
Scheme of data acquisition based on industrial Ethernet
Microcomputer Information
(2008)
L Wang et al.
The development and application of the data acquisition system
Electrical Measurement & Instrumentation
(2004)
Data acquisition and industrial communication
Maschinen Markt
(2002)
MY Jiao et al.
Research on Java rule engine technology
Computer & Information Technology
(2006)

There are more references available in the full text version of this article.

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A big data acquisition engine based on rule engine

Abstract

Scheme of data acquisition based on industrial Ethernet

Microcomputer Information

The development and application of the data acquisition system

Electrical Measurement & Instrumentation

Data acquisition and industrial communication

Maschinen Markt

Research on Java rule engine technology

Computer & Information Technology