Sciweavers

10106 search results - page 74 / 2022
» Algorithm Selection and Scheduling
Sort
View
96
Voted
CP
1997
Springer
15 years 4 months ago
Five Pitfalls of Empirical Scheduling Research
A number of pitfalls of empirical scheduling research are illustrated using real experimental data. These pitfalls, in general, serve to slow the progress of scheduling research b...
J. Christopher Beck, Andrew J. Davenport, Mark S. ...
137
Voted
CCGRID
2008
IEEE
15 years 2 months ago
Scheduling Dynamic Workflows onto Clusters of Clusters using Postponing
In this article, we revisit the problem of scheduling dynamically generated directed acyclic graphs (DAGs) of multi-processor tasks (M-tasks). A DAG is a basic model for expressin...
Sascha Hunold, Thomas Rauber, Frédér...
IIS
2004
15 years 1 months ago
Genetic Algorithm as an Attributes Selection Tool for Learning Algorithms
Learning algorithms, as NN or C4.5 require adequate sets of examples. In the paper we present the usability of genetic algorithms for selection significant features. Fitness of ind...
Halina Kwasnicka, Piotr Orski
WDAG
2007
Springer
127views Algorithms» more  WDAG 2007»
15 years 6 months ago
A Distributed Maximal Scheduler for Strong Fairness
Abstract. Weak fairness guarantees that if an action is continuously enabled, it is executed infinitely often. Strong fairness, on the other hand, guarantees that actions that are...
Matthew Lang, Paolo A. G. Sivilotti
72
Voted
CCGRID
2009
IEEE
15 years 7 months ago
Developing Scheduling Policies in gLite Middleware
We describe our experiences from implementing and integrating a new job scheduling algorithm in the gLite Grid middleware and present experimental results that compare it to the e...
A. Kretsis, Panagiotis C. Kokkinos, Emmanouel A. V...