Big Data Europe 2nd Workshop in Enegry, Brussels 4/10/2016

1. Big Data Europe
System Monitoring: Data acquisition challenge
BigDataEurope 2nd SC3 Workshop, Brussels 4/10/164-oct.-16
D. Foussekis, F. Mouzakis (CRES)

2. BigDataEurope 2nd SC3 Workshop, Brussels 4/10/16
System monitoring p.2
General requirements in System monitoring
 Modular distributed system using standard Ethernet network.
 Specs compliant with International Standards.
 Robust and reliable for 24/7 standalone non-stop operation.
 Scalable and reconfigurable.
 Time Synchronization across all modules (GPS or Master module).
 Embedded processing capabilities.
 Send notifications and alarms.
 Data storage
www.big-data-europe.eu

3. BigDataEurope 2nd SC3 Workshop, Brussels 4/10/16
System monitoring p.3
Typical DAQ system core component (1/2)
 NI-CompactRIO platform http://www.ni.com/compactrio/
 Designed for harsh environments
-20º to -55ºC temperature, 5grms vibration, 30g shock
 Low power requirements
~10W at 9-30V for battery powered standalone operation
 Data acquisition based on FPGA hardware offering fast I/O response times
and increased reliability
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Source: NI.com

4. BigDataEurope 2nd SC3 Workshop, Brussels 4/10/16
System monitoring p.4
Typical DAQ system core component (2/2)
 Various modules for Analogue I/O and Digital I/O
High precision (24-bit delta-sigma) A/D converters (s.g. modules)
16-bit 100kHz Simultaneous Sampling AI modules.
 XML - Configuration file
 Raw (high speed) data sent over the Ethernet and stored on a NAS.
 All data packets are time-stamped with common GPS or local time.
 Backup storage on each module USB port, in case of network loss.
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Source: NI.com

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System monitoring p.5
Typical CMS configuration
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. . .
Gigabit Local Area Network (LAN)
Network Attached Storage (NAS)System Monitoring PC

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System monitoring p.6
Distributed system
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Photo: Courtesy of Vestas Wind Systems A/S
Tower (bending)Tower (torsion)
Electrical generator Gearbox
Blades

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System monitoring p.7
Architecture
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Real-Time microprocessor:
• Runs a real-time OS (NI Linux Real-Time)
• Communicates and uploads data
• Performs statistical analysis
• Stores and compresses raw data
FPGA microprocessor:
• Acquires signals (analogue & digital I/O)
• Runs without OS at high clock rates and no
jitter
• Executes different tasks with true parallelism
• Performs low-level signal processing
(i.e.: filtering, control)
• Assures non-stop operation
Source: NI.com

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System monitoring p.8
Field-Programmable Gate Array (FPGA)
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- Reconfigurable Hardware chip.
- Analogous to a printed circuit board with unconnected components on it.
- Connections in an FPGA circuit are dynamically defined in software.

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System monitoring p.9
Example of FPGA implementation
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Boolean operations (green lines) based on
digital I/O (A,B,C,D,F) execute in parallel with
math operations (orange lines) based on
analogue I/O (W, X, Y, Z).
The compiler produces an optimized bitstream
file, with all the routing paths, between millions
of logic gates, memory blocks and I/O channels.

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System monitoring p.10
Raw Data storage – Existing File Formats
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ASCII files
Characteristics
• Human-readable
• Easily portable to other applications such as
Microsoft Excel
Considerations
• Significantly larger disk footprint
• Slow read and write

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System monitoring p.11
Raw Data storage – Existing File Formats
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Binary files
Characteristics
• Compact file size
• Fast streaming (read & write)
Considerations
• Not human-readable
• Not easily exchangeable

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System monitoring p.12
Raw Data storage – Existing File Formats
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XML files
Characteristics
• Stores complex data structures
• Shows display in a Web browser or in a text
editor
Considerations
• Even larger disk footprint
• Front-end schema design
• Does not stream

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System monitoring p.13
Raw Data storage – Existing File Formats
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Database files
Characteristics
• Store data centrally
• Organize and query test results with MySQL
or Access
Considerations
• Time intensive startup effort
• Requires maintenance
• Potentially high cost

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System monitoring p.14
Raw Data storage – Existing File Formats
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Binary Structured (TDMS – NI Technical Data Management Technology)
Characteristics
• Single streaming binary file
• Three levels of hierarchy for better organization
File, groups, and channels
• Customizable, descriptive properties at each level
• User-defined Meta data for campaign properties
Considerations
• Third party format

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System monitoring p.15
File Format Comparison
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System monitoring p.16
(Instead of) Conclusion
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Ron Musick
Lead Researcher at Lawrence Livermore
National Laboratory