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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thank you!