Task scheduling problem in grid is NP-hard

and it is difficult to attain an optimal solution

so we can use intelligent optimization algorithms to approximate the optimal solution (for example ant colony optimization).Moreover

Quality of Service(QoS)is also an important factor in determining the performance of grid.Task scheduling needs to satisfy user's QoS requirements.In this paper

we propose a novel Multiple QoS Dimensions (QIACO) algorithm for Grid Task Scheduling which is based on modified ant colony optimization algorithm and focuses on the task with QoS dimensions.The QIACO strategy use the ant colony algorithm to solve the task scheduling problem of grid

specifying 5 kinds of QoS dimensions and transforming the QoS to utility

and ultimately

representing the model of task scheduling with multiple QoS dimensions.At the same time

we improve many aspects of the ant colony algorithm

such as the search strategy

decision rule

pheromone update strategy of ant colony optimization

in order to maximize the user's satisfaction.QIACO shows a significant improvement in both makespan and total utility according to the theoretical analysis and simulation.