Grid Scheduling Optimisation
Grid Scheduling Optimisation: Job scheduling plays a critical role in effectively utilising resources in grid computing environments. This project utilises genetic algorithms for grid scheduling optimisation. Building on divisible load theory, a predictable grouped genetic algorithm (PGGA) has been implemented. Compared with other scheduling algorithms such as traditional genetic algorithms (TGA), first-come-first-serve (FIFS) or random scheduling, the FGGA is more effective in job scheduling in grid environments.
A Performance Comparison of four Job Scheduling Algorithms.
For more information on this project, please contact Dr Rick Li.
