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Efficient Conflict Graph Creation for Time-Sensitive Networks with Dynamically Changing Communication Demands

Heiko Geppert, Frank Dürr, Kurt Rothermel

TL;DR

A randomized selection process that reduces the overall size of the graph in half and three heuristics to improve the scheduling success is presented, showing substantial improvements in the graph creation speed and the scheduling success compared to existing work.

Abstract

Many applications of cyber-physical systems require real-time communication: manufacturing, automotive, etc. Recent Ethernet standards for Time Sensitive Networking (TSN) offer time-triggered scheduling in order to guarantee low latency and jitter bounds. This requires precise frame transmission planning, which becomes especially hard when dealing with many streams, large networks, and dynamically changing communications. A very promising approach uses conflict graphs, modeling conflicting transmission configurations. Since the creation of conflict graphs is the bottleneck in these approaches, we provide an improvement to the conflict graph creation. We present a randomized selection process that reduces the overall size of the graph in half and three heuristics to improve the scheduling success. In our evaluations we show substantial improvements in the graph creation speed and the scheduling success compared to existing work, updating existing schedules in fractions of a second. Additionally, offline planning of 9000 streams was performed successfully within minutes.

Efficient Conflict Graph Creation for Time-Sensitive Networks with Dynamically Changing Communication Demands

TL;DR

A randomized selection process that reduces the overall size of the graph in half and three heuristics to improve the scheduling success is presented, showing substantial improvements in the graph creation speed and the scheduling success compared to existing work.

Abstract

Many applications of cyber-physical systems require real-time communication: manufacturing, automotive, etc. Recent Ethernet standards for Time Sensitive Networking (TSN) offer time-triggered scheduling in order to guarantee low latency and jitter bounds. This requires precise frame transmission planning, which becomes especially hard when dealing with many streams, large networks, and dynamically changing communications. A very promising approach uses conflict graphs, modeling conflicting transmission configurations. Since the creation of conflict graphs is the bottleneck in these approaches, we provide an improvement to the conflict graph creation. We present a randomized selection process that reduces the overall size of the graph in half and three heuristics to improve the scheduling success. In our evaluations we show substantial improvements in the graph creation speed and the scheduling success compared to existing work, updating existing schedules in fractions of a second. Additionally, offline planning of 9000 streams was performed successfully within minutes.

Paper Structure

This paper contains 29 sections, 3 equations, 7 figures, 1 table.

Figures (7)

  • Figure 1: Example system. The blue stream has a frame size of 500 and a period of 200µs. The green and yellow streams both have frame sizes of 250 and periods 100µs.
  • Figure 2: Example network with 3 simplified time-triggered streams. Conflicts happen at the network links $\alpha$, $\beta$, $\gamma$, and $\delta$.
  • Figure 3: Conflict graph for the network and streams depicted in Figure \ref{['fig:networkExample']}.
  • Figure 4: Comparison of randomized vs deterministic phase enumeration in a Waxman network with 49 bridges.
  • Figure 5: Stream rejection on a 7x7 grid when the streams have harmonic periods.
  • ...and 2 more figures