Graphs and algorithms
Algorithms and complexity
Heuristic Algorithms for Task Assignment in Distributed Systems
IEEE Transactions on Computers
The Influence of Different Workload Descriptions on a Heuristic Load Balancing Scheme
IEEE Transactions on Software Engineering
Graphs: theory and algorithms
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A taxonomy of scheduling in general-purpose distributed computing systems
IEEE Transactions on Software Engineering
Experiments with Scheduling Using Simulated Annealing in a Grid Environment
GRID '02 Proceedings of the Third International Workshop on Grid Computing
A Scheduling Model for Grid Computing Systems
GRID '01 Proceedings of the Second International Workshop on Grid Computing
Metaheuristics for Group Shop Scheduling
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Structural Complexity and Neural Networks
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
IPDPS '00/JSSPP '00 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
An Empirical Investigation of Load Indices for Load Balancing Applications
Performance '87 Proceedings of the 12th IFIP WG 7.3 International Symposium on Computer Performance Modelling, Measurement and Evaluation
NP-complete scheduling problems
Journal of Computer and System Sciences
Agents, clusters and components: A synergistic approach to the GSP
Future Generation Computer Systems
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In this paper, we study a high-performance Heterogeneous Distributed System (HDS) that is employed as a computing platform or grid. Precisely, we study the problem of scheduling a large number of CPU-intensive tasks on such systems. In this study, the time spent by a task in the system is considered as the main issue that needs to be minimized. The proposed techniques of scheduling dynamic tasks consist of two heuristic algorithms; Recursive Neighbor Search (RNS) and Augmented Tabu-Search (ATS) algorithm. Our technique does not address directly the load-balancing problem since it is completely unrealistic in such large environments, but we will show that even a nonperfectly load-balanced system can behave reasonably well by taking into account the tasks' time demands. These algorithms are compared to a well known scheduling algorithm, in order to compare, evaluate, and clarify their performance.