Paper Info
Title
Comparison of Batch Scheduling for Identical Multi-Tasks Jobs on Heterogeneous Platforms
Abstract
In this paper we consider the scheduling of a batch of the same job on a heterogeneous execution platform. A job is represented by a directed acyclic graph without forks (intree) but with typed tasks. The execution resources are distributed and each resource can carry out a set of task types. The objective function is to minimize the makespan of the batch execution. Three algorithms are studied in this context: an on-line algorithm, a genetic algorithm and a steady-state algorithm. The contribution of this paper is on the experimental analysis of these algorithms and on their adaptation to the context. We show that their performances depend on the size of the batch and on the characteristics of the execution platform.
Year
DOI
Venue
2008
10.1109/PDP.2008.50
PDP
Keywords
Field
DocType
acyclic graph,on-line algorithm,batch execution,genetic algorithm,execution resource,steady-state algorithm,execution platform,objective function,experimental analysis,identical multi-tasks jobs,heterogeneous platforms,heterogeneous execution platform,genetic algorithms,steady state,directed acyclic graph,grid computing,directed graphs,batch scheduling,scheduling,online algorithm
Online algorithm,Job shop scheduling,Scheduling (computing),Computer science,Portable Batch System,Parallel computing,Directed graph,Directed acyclic graph,Job scheduler,Genetic algorithm,Distributed computing
Conference
ISSN
Citations 
PageRank 
1066-6192
4
0.44
References 
Authors
9
3
Name
Order
Citations
PageRank
Sekou Diakite140.44
Jean-Marc Nicod29518.10
Laurent Philippe37112.95