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Parallel Extremal Optimization with Guided State Changes Applied to Load Balancing

  • Ivanoe De Falco
  • Eryk Laskowski
  • Richard Olejnik
  • Umberto Scafuri
  • Ernesto Tarantino
  • Marek Tudruj
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9028)

Abstract

The paper concerns parallel methods for Extremal Optimization (EO) applied for processor load balancing for distributed programs. In these methods the EO approach is used which is parallelized and extended by a guided search of next solution state. EO detects the best strategy of tasks migration leading to a reduction in program execution time. We assume a parallel improvement of the EO algorithm with guided state changes which provides a parallel search for a solution based on two step stochastic selection during the solution improvement based on two fitness functions. The load balancing improvements based on EO aim at better convergence of the algorithm and better quality of program execution in terms of the execution time. The proposed load balancing algorithm is evaluated by experiments with simulated parallelized load balancing of distributed program graphs.

Keywords

Distributed program design Extremal optimization Load balancing Parallel computing 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ivanoe De Falco
    • 1
  • Eryk Laskowski
    • 2
  • Richard Olejnik
    • 3
  • Umberto Scafuri
    • 1
  • Ernesto Tarantino
    • 1
  • Marek Tudruj
    • 2
    • 4
  1. 1.Institute of High Performance Computing and Networking, CNRNaplesItaly
  2. 2.Institute of Computer Science, Polish Academy of SciencesWarsawPoland
  3. 3.Computer Science LaboratoryUniversity of Science and Technology of LilleVilleneuve-d’AscqFrance
  4. 4.Polish-Japanese Institute of Information TechnologyWarsawPoland

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