To handle user requests coming from all over the world, online services need to schedule resources to fulfill the corresponding stochastic demands for various resources in geo-distributed data centers. In order to make full use of the advantages of cloud resources and tap the potential of private infrastructure, the optimal schedule plan should consider the heterogeneity of different kinds of data centers. It results in a highly complex non-linear programming problem. To find efficient solutions, we introduce a related and simple problem to quickly obtain a feasible solution close to optimal one, and then leverage a differential evolution process with special steps to solve it quickly. By testing the algorithm using simulated and realistic data, we find that our algorithm outperforms the existing algorithms and can increase the revenue by more than 34%.

为了处理来自世界各地的用户请求，在线服务需要安排资源来满足地理分布式数据中心对各种资源的相应随机需求。为了充分利用云资源的优势并挖掘私有基础架构的潜力，最佳计划计划应考虑各种数据中心的异构性。这导致高度复杂的非线性编程问题。为了找到有效的解决方案，我们引入了一个相关的简单问题来快速获得接近最佳解决方案的可行解决方案，然后利用带有特殊步骤的差分演化过程来快速解决该问题。通过使用模拟和真实数据测试算法，