A new algorithm for grid independent task schedule: Genetic simulated annealing

Task schedule is a critical issue of distributed computing. Foster et al. (2001) defined "Grid problem", which is defined as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources -what they referred to as virtual organizations (VO). Improving the performance of grid computing relies much on the grid task scheduling algorithm. In this paper, a new genetic simulated annealing (GSA) algorithm which combines genetic algorithm (GA) with simulated annealing (SA) algorithm for grid task scheduling is proposed, it could avoid trapping in a local minimum effectively and get the global optimization at last. The algorithm performs better than genetic algorithm and simulated annealing algorithm respectively.