Supplementary material for the paper Scheduling Constrained-Deadline Sporadic Parallel

Abstract

Finding a solution to the MILP expressed by Fig. 3 and Fig. 5 is challenging because (i) the number of variables and constraints is large and (ii) BIG is much larger than the other constants causing numerical issues. Therefore, we will rewrite the MILP to avoid numerical issues. We will also present different methods for solving the MILP; they differ in (i) the amount of time to finish and (ii) whether a solution is guaranteed to be found if a solution exists. They all have in common, however, that they return a tuple hag; oi such that if ag is true, then the MILP is feasible.

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Document Details

Document Type
Technical Report
Publication Date
Oct 18, 2014
Accession Number
ADA613941

Entities

People

  • Bjorn A. Andersson

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Abstracts
  • Department Of Defense
  • Engineering
  • Guarantees
  • Information Operations
  • Law
  • Materials
  • Optimization
  • Parallel Computing
  • Parallel Processing
  • Scheduling (Production)
  • Sensor Fusion
  • Software Development
  • Test And Evaluation
  • United States
  • Universities

Readers

  • Nanocomposite Materials Science
  • Operations Research
  • Systems Analysis and Design