A Hybrid Algorithm for DAG Application Scheduling on Computational Grids

  • Lyes Bouali
  • Karima Oukfif
  • Samia BouzefraneEmail author
  • Fatima Oulebsir-Boumghar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9395)


In the late three decades, grid computing has emerged as a new field providing a high computing performance to solve larger scale computational demands. Because Directed Acyclic Graph (DAG) application scheduling in a distributed environment is a NP-Complete problem, meta-heuristics are introduced to solve this issue. In this paper, we propose to hybridize two well-known heuristics. The first one is the Heterogeneous Earliest Finish Time (HEFT) heuristic which determines a static scheduling for a DAG in a heterogeneous environment. The second one is Particle Swarm Optimization (PSO) which is a stochastic meta-heuristic used to solve optimization problems. This hybridization aims to minimize the makespan (i.e., overall completion time) of all the tasks within the DAG. The experimental results that have been conducted under hybridization show that this approach improves the scheduling in terms of completion time compared to existing algorithms such as HEFT.


Grid computing Task scheduling Directed acyclic graph Heterogeneous earliest finish time algorithm Particle swarm optimization algorithm Makespan 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lyes Bouali
    • 1
  • Karima Oukfif
    • 2
    • 3
  • Samia Bouzefrane
    • 4
    Email author
  • Fatima Oulebsir-Boumghar
    • 3
  1. 1.LARI LaboratoryUMMTOTizi OuzouAlgeria
  2. 2.Compute Science DepartmentUMMTOTizi OuzouAlgeria
  3. 3.LRPE LaboratoryUSTHBBab EzzouarAlgeria
  4. 4.CEDRIC LaboratoryCNAMParisFrance

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