iDynamics: A Configurable Emulation Framework for Evaluating Microservice Scheduling Policies under Controllable Cloud-Edge Dynamics
For researchers and practitioners in cloud-edge computing, iDynamics provides a tool to systematically evaluate scheduling policies under realistic, controllable dynamics, addressing the lack of reproducibility in current evaluations.
iDynamics is a configurable emulation framework for evaluating microservice scheduling policies under controllable cloud-edge dynamics. It enables reproducible experiments with real microservice code, demonstrating that call-graph-aware and hybrid policies can mitigate SLA violations under dynamic network conditions.
This paper presents iDynamics, a configurable emulation framework that exposes these dynamics as controllable experimental factors while running real microservice code on a Kubernetes-based cloud-edge cluster. iDynamics comprises three modular components. The Graph Dynamics Analyzer reconstructs application call graphs from service-mesh telemetry and quantifies bidirectional traffic between upstream-downstream microservice pairs. The Networking Dynamics Manager injects and measures realistic cross-node delay and bandwidth patterns via Linux traffic control primitives and distributed agents. The Scheduling Policy Extender offers a pluggable interface and utility library for implementing and evaluating arbitrary scheduling policies, expressed as pod placement and migration strategies. We use iDynamics to implement two representative policies -- a call-graph-aware policy and a hybrid policy that jointly considers traffic and latency -- as case studies demonstrating how the framework can be used to study SLA compliance under dynamic conditions. Experiments on a real cloud-edge cluster, running the DeathStarBench Social Network microservices, show that iDynamics can accurately emulate targeted network conditions, generate diverse call-graph and traffic patterns, and help quantify how different scheduling policies mitigate SLA violations under controllable and repeatable dynamics.