Automatic determination of grain size for efficient parallel processing
Communications of the ACM - Special issue: multiprocessing
Scheduling problems and traveling salesman: the genetic edge recombination
Proceedings of the third international conference on Genetic algorithms
Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Clustering task graphs for message passing architectures
ICS '90 Proceedings of the 4th international conference on Supercomputing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Using Genetic Algorithms to Schedule Flow Shop Releases
Proceedings of the 3rd International Conference on Genetic Algorithms
Sizing Populations for Serial and Parallel Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
A Comparison of Heuristics for Scheduling DAGs on Multiprocessors
Proceedings of the 8th International Symposium on Parallel Processing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 1 - Volume 02
Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems
Computers and Operations Research
Hybrid meta-heuristics algorithms for task assignment in heterogeneous computing systems
Computers and Operations Research
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Scheduling a directed acyclic graph (DAG) which represents the precedence relations of the tasks of a parallel program in a distributed computing system (DCS) is known as an NP-complete problem except for some special cases. Many heuristic-based methods have been proposed under various models and assumptions. A DCS can be classified in two types according to the characteristics of the processors on a network: a distributed homogeneous system (DHOS) and a distributed heterogeneous system (DHES). The paper defines a general model for a DHOS and a DHES and presents a genetic algorithm (GA) to solve the task scheduling problem in the defined DCS. The performance of the proposed GA is compared with the list scheduling algorithm in a DHOS and with the one-level reach-out greedy algorithm (OLROG) in a DHES. The proposed GA has shown better performance in various environments than other scheduling methods.