Process Scheduling Using Ant Colony Optimization Techniques

  • Bruno Rodrigues Nery
  • Rodrigo Fernandes de Mello
  • André Carlos Ponce de Leon Ferreira de Carvalho
  • Laurence Tianruo Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4330)


The growing availability of low cost microprocessors and the evolution of computing networks have enabled the construction of sophisticated distributed systems. The computing capacity of these systems motivated the adoption of clusters to build high performance solutions. The improvement of the process scheduling over clusters originated several proposals of scheduling and load balancing algorithms. These proposals have motivated this work, which defines, evaluates and implements a new load balancing algorithm for heterogeneous capacity clusters. This algorithm, named Ant Scheduler, uses concepts of ant colonies for the development of optimization solutions. Experimental results obtained in the comparison of Ant Scheduler with other approaches investigated in the literature show its ability to minimize process mean response times, improving the performance.


Schedule Algorithm Load Balance Parallel Application Load Information Load Balance Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bruno Rodrigues Nery
    • 1
  • Rodrigo Fernandes de Mello
    • 1
  • André Carlos Ponce de Leon Ferreira de Carvalho
    • 1
  • Laurence Tianruo Yang
    • 2
  1. 1.Instituto de Ciências Matemáticas e de ComputaçãoUniversidade de São PauloSão CarlosBrazil
  2. 2.St. Francis Xavier UniversityAntigonishCanada

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