While various service orchestration aspects within Computing Continuum (CC) systems have been extensively addressed, including service placement, replication, and scheduling, an open challenge lies in ensuring uninterrupted data delivery from IoT devices to running service instances in this dynamic environment, while adhering to specific Quality of Service (QoS) requirements and balancing the load on service instances. To address this challenge, we introduce QEdgeProxy, an adaptive and QoS-aware load balancing framework specifically designed for routing client requests to appropriate IoT service instances in the CC. QEdgeProxy integrates naturally within Kubernetes, adapts to changes in dynamic environments, and manages to seamlessly deliver data to IoT service instances while consistently meeting QoS requirements and effectively distributing load across them. This is verified by extensive experiments over a realistic K3s cluster with instance failures and network variability, where QEdgeProxy outperforms both Kubernetes built-in mechanisms and a state-of-the-art solution, while introducing minimal computational overhead.

翻译：尽管计算连续体（CC）系统中的服务编排方面（包括服务部署、复制和调度）已得到广泛研究，但一个悬而未决的挑战在于：如何在动态环境下确保物联网设备向运行中的服务实例不间断传输数据，同时满足特定服务质量（QoS）要求并平衡服务实例负载。为应对这一挑战，我们提出QEdgeProxy——一个专为CC中物联网服务实例客户端请求路由设计的自适应QoS感知负载均衡框架。QEdgeProxy原生集成于Kubernetes，能够适应动态环境变化，在持续满足QoS要求并有效分配负载的同时，实现向物联网服务实例的无缝数据传输。通过在真实K3s集群（含实例故障与网络波动）上的大量实验，验证了QEdgeProxy在引入极低计算开销的前提下，性能优于Kubernetes内置机制及现有最优方案。