With the growing demand of data processing/storage from Internet of Things (IoT) users and the increasing maturity of Cloud-Edge technologies, it becomes more and more critical to develop an effective and efficient performance evaluation approach in order to enhance the performance of Cloud-Edge services. Analytic modeling is an effective evaluation approach. The existing modeling researches on edge and/or cloud computing either ignored workload heterogeneity or ignored delay constraint of IoT tasks. This paper develops a hierarchical model for capturing the behaviors of Cloud-Edge datacenters, which provides service to tasks with different service priorities and requesting different number of service resources. Formulas for calculating performance measures of interest are also developed. The approximate accuracy of the proposed analytic model is verified through comparing numerical results and discrete-event simulation results.

随着物联网（IoT）用户对数据处理/存储的需求不断增长，以及Cloud-Edge技术的日趋成熟，开发有效，高效的性能评估方法以增强Cloud的性能变得越来越重要。 -边缘服务。分析建模是一种有效的评估方法。边缘和/或云计算的现有模型研究要么忽略了工作负载异构性，要么忽略了IoT任务的延迟约束。本文开发了一种用于捕获Cloud-Edge数据中心行为的分层模型，该模型为具有不同服务优先级和请求不同数量服务资源的任务提供服务。还开发了用于计算目标绩效指标的公式。