Playing games with scenario- and resource-aware SDF graphs through policy iteration

  • Authors:

  • Yang Yang;Marc Geilen;Twan Basten;Sander Stuijk;Henk Corporaal

  • Affiliations:

  • Eindhoven University of Technology, Netherlands;Eindhoven University of Technology, Netherlands;Eindhoven University of Technology, Netherlands and Embedded Systems Institute, Eindhoven, Netherlands;Eindhoven University of Technology, Netherlands;Eindhoven University of Technology, Netherlands

  • Venue:
  • DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2012

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Abstract

The two-player mean-payoff game is a well-known game theoretic model that is widely used, for instance in economics and control theory. For controller synthesis, a controller is modeled as a player while the environment, or plant, is modeled as the opponent player (adversary). Synthesizing an optimal controller that satisfies a given criterion corresponds to finding a winning strategy for the controller player. Emerging streaming applications (audio, video, communication, etc.) for embedded systems exhibit both input sensitive and controller sensitive runtime behavior, where the controller's role is run-time management or scheduling. Embedded controllers need to be optimized for dynamic inputs, while guaranteeing throughput constraints. In this paper, we consider this design task for scenario- and resource-aware dataflow graphs that model streaming applications. Scenarios in these models capture classes of dynamic environment behavior. We demonstrate how to model and solve the controller synthesis problem by constructing a winning strategy in a two-player mean payoff throughput game.