On the Scalability of Constraint Solving for Static/Off-Line Real-Time Scheduling

Abstract

Abstract. Recent papers have reported on successful application of constraint solving techniques to off-line real-time scheduling problems, with realistic size and complexity. Success allegedly came for two reasons: major recent advances in solvers efficiency and use of optimized, problemspecific constraint representations. Our current objective is to assess further the range of applicability and the scalability of such constraint solving techniques based on a more general and agnostic evaluation campaign. For this, we have considered a large number of synthetic scheduling problems and a few real-life ones, and attempted to solve them using 3 state-of-the-art solvers, namely CPLEX, Yices2, and MiniZinc/G12. Our findings were that, for all problems considered, constraint solving does scale to a certain limit, then diverges rapidly. This limit greatly depends on the specificity of the scheduling problem type. All experimental data (synthetic task systems, SMT/ILP models) are provided so as to allow experimental reproducibility.

Instance Generation via Generator Instances

“…The assignment of scores depends on the specific definition of instance grading. In our case, we define graded instances as satisfiable (SAT) and solvable by Minion within [10,300] seconds. We also place a time limit of 5 minutes on Savile Row for the translation from the Essence instance parameter to Minion input format.…”

Correct-by-Construction Parallelization of Hard Real-Time Avionics Applications on Off-the-Shelf Predictable Hardware

“…This article does not provide advances on the complexity of real-time scheduling algorithms. Recent papers provided conflicting evidence-pro [20,45] and contra [26]-on the ability of methods based on constraint solving to find solutions to large-scale real-time scheduling problems. Like most others, the scheduling problem we address can be encoded as an integer linear programming (ILP), satisfiability modulo theories (SMT), or constraint program.…”

Worst-Case Reaction Time Optimization on Deterministic Multi-Core Architectures with Synchronous Languages

“…(1), minimizing T amounts to minimizing t d1 , t d2 , and t s for each task τ i,j . It is notorious that solving scheduling problems using ILP may lead to scalability issues [33]. However, (i) our problem only depends on the number of cores and not on the number of threads interleaved (see below), and (ii) we only target small to medium-size multi-cores.…”