Conference Paper

Dynamic Task Scheduling using Genetic Algorithms for Heterogeneous Distributed Computing.

DOI: 10.1109/IPDPS.2005.184 Conference: 19th International Parallel and Distributed Processing Symposium (IPDPS 2005), CD-ROM / Abstracts Proceedings, 4-8 April 2005, Denver, CO, USA
Source: DBLP

ABSTRACT An algorithm has been developed to dynamically sched- ule heterogeneous tasks on heterogeneous processors in a distributed system. The scheduler operates in an environ- ment with dynamically changing resources and adapts to variable system resources. It operates in a batch fashion and utilises a genetic algorithm to minimise the total exe- cution time. We have compared our scheduler to six other schedulers, three batch-mode and three immediate-mode schedulers. We have performed simulations with randomly generated task sets, using uniform, normal, and Poisson dis- tributions, whilst varying the communication overheads be- tween the clients and scheduler. We have achieved more effi- cient results than all other schedulers across a range of dif- ferent scenarios while scheduling 10,000 tasks on up to 50 heterogeneous processors.

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