  Aiming at analyzing performance in cloud computing, some unpredictable
perturbations which may lead to performance downgrade are essential factors
that should not be neglected. To avoid performance downgrade in cloud computing
system, it is reasonable to measure the impact of the perturbations, and
further propose a robust scheduling strategy to maintain the performance of the
system at an acceptable level. In this paper, we first describe the
supply-demand relationship of service between cloud service providers and
customers, in which the profit and waiting time are objectives they most
concerned. Then, on the basis of introducing the lowest acceptable profit and
longest acceptable waiting time for cloud service providers and customers
respectively, we define a robustness metric method to declare that the number
and speed of servers should be adequately configured in a feasible region, such
that the performance of cloud computing system can stay at an acceptable level
when it is subject to the perturbations. Subsequently, we discuss the
robustness metric method in several cases, and propose heuristic optimization
algorithm to enhance the robustness of the system as much as possible. At last,
the performances of the proposed algorithm are validated by comparing with DE
and PSO algorithm, the results show the superiority of the proposed algorithm.
