The transition from traditional architectures to containerized microservices within the cloud-edge computing continuum introduces significant challenges, particularly in the efficient scheduling of microservices under dynamic conditions. Complex and fluctuating call-graph dependencies, varying cross-node communication latencies, and unpredictable bandwidth conditions substantially impact the performance and reliability of deployed microservices. Consequently, accurately evaluating scheduling policies in such dynamic environments remains essential yet challenging due to the lack of realistic and controllable evaluation frameworks. In this paper, we propose iDynamics, a novel evaluation framework designed explicitly to address these challenges. iDynamics provides comprehensive and controllable evaluation capabilities by emulating realistic dynamics, including configurable call-graph topologies, cross-node communication delays, and bandwidth variability. The framework is composed of modular components, such as the Graph Dynamics Analyzer, Networking Dynamics Manager, and Scheduling Policy Extender, enabling fine-grained environmental control and facilitating systematic comparisons of different scheduling strategies. Extensive experiments on a real cloud-edge testbed demonstrate that iDynamics effectively captures diverse dynamic scenarios encountered in microservice deployments, offering a robust solution for evaluating and optimizing policy performance under realistic and controllable conditions.

翻译：从传统架构向云边计算连续体中的容器化微服务过渡带来了重大挑战，尤其是在动态条件下高效调度微服务方面。复杂且波动的调用图依赖关系、变化的跨节点通信延迟以及不可预测的带宽条件，显著影响了已部署微服务的性能与可靠性。因此，由于缺乏真实且可控的评估框架，在此类动态环境中准确评估调度策略仍然至关重要且充满挑战。本文提出iDynamics，一个专门为解决这些挑战而设计的新型评估框架。iDynamics通过模拟真实动态，包括可配置的调用图拓扑、跨节点通信延迟和带宽可变性，提供了全面且可控的评估能力。该框架由模块化组件构成，如图动态分析器、网络动态管理器和调度策略扩展器，实现了细粒度的环境控制，并促进了不同调度策略的系统性比较。在真实云边测试平台上进行的广泛实验表明，iDynamics能有效捕捉微服务部署中遇到的各种动态场景，为在真实可控条件下评估和优化策略性能提供了一个稳健的解决方案。