Finite-horizon scheduling of radar dwells with online template construction

  • Authors:
  • Sathish Gopalakrishnan;Marco Caccamo;Chi-Sheng Shih;Chang-Gun Lee;Lui Sha

  • Affiliations:
  • Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA;Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA;Department of Computer Science and Information Engineering, Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan;Department of Electrical and Computer Engineering, The Ohio State University, Columbus, USA;Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA

  • Venue:
  • Real-Time Systems
  • Year:
  • 2006

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Abstract

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon.