In this chapter, we review a few important concepts from Grid computing related to scheduling problems and their resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the heart of any Grid-like computational system. Different types of scheduling based on different criteria, such as static vs. dynamic environment, multi-objectivity, adaptivity, etc., are identified. Then, heuristics and meta-heuristics methods for scheduling in Grids are presented. The chapter reveals the complexity of the scheduling problem in Computational Grids when compared to scheduling in classical parallel and distributed systems and shows the usefulness of heuristics and meta-heuristics approaches for the design of efficient Grid schedu...
Abstract: Various aspects of the task scheduling in GRID are considered. The possible appr...
In this paper we present the design and implementation of an hyper-heuristic for efficiently schedul...
Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Sev...
In this chapter, we review a few important concepts from Grid computing related to scheduling proble...
In this paper we survey computational models for Grid scheduling problems and their resolution using...
The most important goal of the Resource Scheduling in Grid Computing is to efficiently map the jobs ...
Thanks to advances in wide-area network technologies and the low cost of computing resources, Grid c...
Resource management effective scheduling algorithms is also increasing rapidly, particularly in the ...
Computational Grid (CG) is a wide network of computational resources that provides a distributed pla...
Efficient execution of computations in grid can require mapping of tasks to processors whose perform...
AbstractScheduling and resource allocation in large scale distributed environments, such as Computat...
An important problem that arises in the area of grid computing is one of optimally assigning jobs to...
Grid computing provides the means of using and sharing heterogeneous resources that are geographical...
One of the most challenging issues in modelling today's large-scale computational systems is to effe...
Grid computing generally involves the aggregation of geographically distributed resources in the con...
Abstract: Various aspects of the task scheduling in GRID are considered. The possible appr...
In this paper we present the design and implementation of an hyper-heuristic for efficiently schedul...
Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Sev...
In this chapter, we review a few important concepts from Grid computing related to scheduling proble...
In this paper we survey computational models for Grid scheduling problems and their resolution using...
The most important goal of the Resource Scheduling in Grid Computing is to efficiently map the jobs ...
Thanks to advances in wide-area network technologies and the low cost of computing resources, Grid c...
Resource management effective scheduling algorithms is also increasing rapidly, particularly in the ...
Computational Grid (CG) is a wide network of computational resources that provides a distributed pla...
Efficient execution of computations in grid can require mapping of tasks to processors whose perform...
AbstractScheduling and resource allocation in large scale distributed environments, such as Computat...
An important problem that arises in the area of grid computing is one of optimally assigning jobs to...
Grid computing provides the means of using and sharing heterogeneous resources that are geographical...
One of the most challenging issues in modelling today's large-scale computational systems is to effe...
Grid computing generally involves the aggregation of geographically distributed resources in the con...
Abstract: Various aspects of the task scheduling in GRID are considered. The possible appr...
In this paper we present the design and implementation of an hyper-heuristic for efficiently schedul...
Bio-inspired heuristics have been promising in solving complex scheduling optimization problems. Sev...