Using Bioinspired Meta-heuristics to Solve Reward-Based Energy-Aware Mandatory/Optional Real-Time Tasks Scheduling

  • Matías Micheletto Universidad Nacional del Sur / CONICET
  • Rodrigo Santos Universidad Nacional del Sur / CONICET
  • Javier Orozco Universidad Nacional del Sur / CONICET

Resumo


In this paper we present meta-heuristics to solve the energy aware reward based scheduling of real-time tasks with mandatory and optional parts in homogeneous multi-core processors. The problem is NP-Hard. The meta-heuristics are the bioinspired methods Particle Swarm Optimization and Genetic Algorithm. Results are compared using synthetic systems of tasks, generated following the guidelines proposed in previous papers with an Integer Lineal Programming solution.
Palavras-chave: Optimal scheduling, Genetic algorithms, Program processors, Real-time systems, Processor scheduling, Linear programming, Scheduling, Multicore Systems, Mandatory/Optional Tasks, Energy Handling
Publicado
03/11/2015
Como Citar

Selecione um Formato
MICHELETTO, Matías; SANTOS, Rodrigo; OROZCO, Javier. Using Bioinspired Meta-heuristics to Solve Reward-Based Energy-Aware Mandatory/Optional Real-Time Tasks Scheduling. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 5. , 2015, Foz do Iguaçu/PR. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2015 . p. 1578-1709. ISSN 2237-5430.