Task Scheduling in Grid Environment with ant Colony Method for Cost and Time

In this paper, we would like to propose an improved algorithm for task scheduling in grid environment with metaheuristic ant colony optimization method considering the cost and time parameters fromquality of service. The proposed algorithm is evaluated by using the required cost and time parameters to carry out the task. With implementation these parameters in t he simulate environment, we can create situation that scheduling task will be done with better position and achieve high performance on computational grids. Finally the experiment and simulated results will show that the proposed heuristic scheduling algor ithm performs significantly to ensure high throughput, reduced time and cost . Also proposed algorithmis more efficient in the grid environment. This proposed algorithm is more efficient than theadaptive ACS and MOACO algorithms.