Framework for task scheduling in heterogeneous distributed computing using genetic algorithms

An algorithm has been developed to dynamically schedule heterogeneous tasks on to heterogeneous processors in a distributed system. The scheduling strategy operates in a dynamically changing computing resource environment and adapts to variable communication costs and variable availability of processing resources. The scheduler utilises a genetic algorithm to minimise the overall execution time. Experiments are performed which show that the algorithm can achieve near optimal efficiency, with up to 100,000 tasks being scheduled