A webinar on the Dynamic CEP Specific Enabler (SE) from the FITMAN project. DyCEP enables very complex real-time processing of the shop-floor events and other events relevant for manufacturing process. This SE is based on the Esper4FastData Generic Enabler (GE) from FIWARE. Presented by Nenad Stojanovic from FZI.

1. Welcome to the
FITMAN Specific Enabler Webinar on DyCEP
16th June 2015
Nenad Stojanovic
Aleksandar Stojadinovic
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2. Introduction
• DyCEP - Dynamic CEP
– DyCEP enables very complex real-time processing
of the shop-floor events and other events relevant
for manufacturing process (e.g. from MES).
• Targeted at Smart Factories
• Based on GE Esper4FastData, i.e. it extends the
functionalities of Esper4FastData with more complex
real-time processing.
• Delivered as Storm compatible JAR (however,
source code changes may be needed).
16/06/2015 FITMAN Webinars - June 2015

3. DyCEP - Scope
• One of the main challenges for modern manufacturing is the
possibility to react on particular situations in order to improve the
efficiency of manufacturing or avoid some problems.
• Current systems for real-time processing in manufacturing are
mainly focused on the simple reactivity, i.e. the possibility to define
“simple” situations and react in “one step” on them.
• It is usually implemented through a CEP (Complex Event Processing)
engine. However, more demanding manufacturing of the future will
require “complex” reactivity that is essentially based on the
discovery of complex situations of interest in real-time (zero delay,
or even ahead of time).
• Moreover, in order to cope with very changeable environment
(internal, external) in the manufacturing, the provided processing
infrastructure must support dynamic changes, which is one of the
main challenges for the current data processing infrastructure.
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4. DyCEP vs. CEP
CEP Engine as a central very
powerful processor
CEP as a Network
CEP Engine
input stream
input streams
Complex
Real-time
Processing
Network
Condition
Processing 1
Condition
Processing 2
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5. DyCEP – the structure
• For the case of envisioned dynamic monitoring
new processing capabilities are requested, esp. in
the context of processing pipelines, i.e. enabling
complex processing networks.
• DyCEP assumes several processing elements
which are connected in the way that ensures
maximal efficiency of the processing task.
• This infrastructure is based on the Storm, the
architecture for real-time (streaming) data
processing. It uses custom created "spouts" and
"bolts" to define information sources and
manipulations to allow real-time distributed
processing of streaming data.
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6. DyCEP – the goal
• Ultimate goal: Discover a complex real-time
situation of interest timely (zero delay, or
even ahead of time)
• Subgoals:
1. Define the situation of interest properly
2. Organize data-driven detection process efficiently
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7. DyCEP – the characteristics
• Main advantage of the approach is the possibility
to change the patterns deployed in the CEP
engines (embedded in bolts).
• In that way we ensure that the processing
infrastructure will be able to follow the dynamics
of input data.
• In addition, such an approach will enable
continuous improvement of the detection
process that is very important for decreasing the
number of false positive, which is one of the
biggest problems for real-time processing
approaches.
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8. DyCEP - Architecture
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9. DyCEP – components (1/2)
• Broker is the mechanism for enabling
subscriptions for relevant events by DyCEP (pub-
sub functionality).
• Web API is responsible for getting input data in
the DyCEP. It satisfies NGSI10 interface, as
requested by FI PPP infrastructure. The format of
data follows the specification provided by use
case partners
• Simple event handling spout enables receiving
events of interest and forwarding them to the
rest of the processing network
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10. DyCEP – components (2/2)
• Esper4FastData is FIWARE GE responsible for complex
event processing (realized as external service, offered from
a bolt). Outcome is realized through a web service.
– responsible for static processing that requires simple complex
event patterns and shouldn’t scale (because of the limited data
input)
• ESPER-1 is the CEP engine hosted in a bolt (in contrast to
Esper4FastData – realized as external service). Outcome is
realized through a web service. In addition notifications can
be pushed to mobile devices.
– responsible for complex situations and prepared for horizontal
scaling (by being hosted in a bolt, so that several bolt instances
can be generated on demand
• GCM Push Bolt enables usage of the Google service for
pushing notification to mobile devices
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11. DyCEP – patterns
• The creation of the CEP patterns can be done
in the manual way, or using a specialized
mobile-based pattern editor provided by
Nissatech.
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12. DyCEP – input
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13. TRW use case: Processing pipeline
1. Worker
2. Kinect motion
sensing unit
3. Workstation
controlling the
Kinect sensor
4. Web service
interface to the
CEP topology
5. Storm topology
with CEP
6. Some system
called on a
notification
from the CEP
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14. Provisioning
• As a Virtual Machine image
– VirtualBox Sandbox version: deploy on any Linux,
Windows, MacOS system for experiments -
ftp://repo.nimbus-ware.com/fitman-dycep.zip
• As source code
– SourceForge:
http://catalogue.fitman.atosresearch.eu/sites/default
/files/storage/enablers/StormCEP-src-0.1.zip
• Source compiled to a JAR and deployed to a
Storm cluster is the preferred provisioning way
• Note: Esper4Fast data distribution not included
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15. Terms and conditions
• Within the scope of the FI-PPP Programme
– Free use of the software for members till the end
of the Programme
– FITMAN provides free support to members till the
end of the Programme
• Out of FI-PPP Programme scope
– All software assets are free and Open Source
(GPLv2 license applies globally)
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16. Q & A
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17. Thank you!
16/06/2015 FITMAN Webinars - June 2015