Adaptive task scheduling based on Multi Criterion Ant Colony Optimization in computational grids

Abstract

Grid Computing is a form of distributed computing environment that allows sharing, selection and coordinated use of diverse resources owned by different organizations. Effective and efficient scheduling of resources in grid is fundamentally important. To optimize the scheduling of tasks to suitable resources in computational grids, a Multi Criterion Ant Colony Optimization (MCACO) Algorithm is proposed. From the experimental results and analysis it is evaluated that the adaptive task scheduling using MCACO has a faster convergence in task scheduling with minimal makespan and flowtime.