1. Technical University of Cluj-Napoca
Reservation-Based Data Flow Scheduling in Distributed Control Applications
A. Hangan, R. Marfievici,
Gh. Sebestyen
Technical University of Cluj-Napoca

2. Overview Introduction
Network communication in distributed control systems
The data flow model
Communication scheduling
The industrial control application and the device simulator
Experimental results
Conclusion
12/3/2018
ICNS'07 Athens, Greece

3. Introduction New requirements imposed for distributed control systems
Remote process supervision and control
Remote deployment
On-line reports, etc.
The use of the Internet as communication infrastructure
IPv6 communication infrastructure for reliable and secure real-time data transmission
12/3/2018
ICNS'07 Athens, Greece

4. Network communication in distributed control systems
Real-time constraints
Message delivery time control mechanisms to guarantee maximum delivery time
Predictability of network behavior
Delivery efficiency of short messages over the Internet
Control device interoperability
12/3/2018
ICNS'07 Athens, Greece

5. The data flow model
Models traffic between control applications and devices as a sum of periodic and a-periodic data flows
Data flow = sum of all packets sent through the network that have the same source, destination, content and periodicity
Periodic and a-periodic data flows
12/3/2018
ICNS'07 Athens, Greece

6. The data flow model (contd.)
Solves:
Efficiency of short control message delivery over the Internet – merge similar data flows to increase packet payload
Device interoperability – use of XML data flow specification
12/3/2018
ICNS'07 Athens, Greece

7. Communication scheduling
Transmission time control solved through bandwidth reservation
Analysis of data flows to determine required bandwidth
Resource reservation signaling using Resource Reservation Protocol (RSVP)
12/3/2018
ICNS'07 Athens, Greece

8. Communication scheduling (contd.)
Variables used for data flow analysis:
Round-trip time between source and destination (RTT)
Transmission time of packets that belong to the data flow (C)
Data flow period of occurrence (T)
Data flow priority (P)
Data flow deadline (D)
Data flow response time (r)
Transmission time of packets that belong to data flows with higher priority
Maximum transmission time of packets that belong to data flows with lower priority
12/3/2018
ICNS'07 Athens, Greece

9. Communication scheduling (contd.)
Response time
equations:
Transmission time
equation:
Response time obtained through iteration, until r(t+1)=r(t)
Communication scheduling is feasible only if the computed response time is less than the flow’s deadline (r<D)
Bandwidth is computed by applying the feasibility condition r<D
12/3/2018
ICNS'07 Athens, Greece

10. The industrial control application and the device simulator
Industrial control application functions:
Remote process control and visualization
Use of middleware facilities
Data flow definitions for devices
Data flow control through commands
Negotiation of resources
Receive and process data flows
Device simulator functions:
Receive commands from control application
Send periodical data flows according to specifications
Generate process values
12/3/2018
ICNS'07 Athens, Greece

11. Experimental results IPv4 scenario: IPv6 scenario:
PC systems configured as nodes
2 routers
Software installed: industrial communication middleware, industrial application, device simulators; modified for IPv4
Process schema with 2 data flows: Flow 1 (T=2s); Flow 2 (T=0.5s)
Total bandwidth: 100Mbps
IPv6 scenario:
PC systems configured as nodes
2 routers
Software installed: industrial communication middleware, industrial application, device simulators
Process schema with 2 data flows: Flow 1 (T=2s); Flow 2 (T=0.5s)
Total bandwidth: 64Mbps
12/3/2018
ICNS'07 Athens, Greece

12. Experimental results (contd.)
Response time measurements on IPv6 infrastructure
12/3/2018
ICNS'07 Athens, Greece

13. Experimental results (contd.)
Response time measurements on IPv4 infrastructure
12/3/2018
ICNS'07 Athens, Greece

14. Conclusion
New approach in solving network delivery time control, data delivery efficiency and device interoperability in distributed control systems
The proposed method is able to satisfy the real-time constraints
Analytical evaluation of response time was an upper limit to measured delivery time
12/3/2018
ICNS'07 Athens, Greece

15. Thank you!