Common deployment models for Edge Computing are based on (composable) microservices that are offloaded to cloudlets. Runtime adaptations-in response to varying load, QoS fulfillment, mobility, etc.-are typically based on coarse-grained and costly management operations such as resource re-allocation or migration. The services themselves, however, remain non-adaptive, worsening the already limited elasticity of Edge Computing compared to Cloud Computing. Edge computing applications often have stringent requirements on the execution time but are flexible regarding the quality of a computation. The potential benefits of exploiting this trade-off remain untapped. This paper introduces the concept of adaptable microservices that provide alternative variants of specific functionalities. We define so-called service variants that differ w.r.t. the internal functioning of the service, manifested in different algorithms, parameters, and auxiliary data they use. Such variants allow fine-grained trade-offs between the QoS (e.g., a maximum tolerable execution time) and the quality of the computation. We integrate adaptable microservices into an Edge Computing framework, show the practical impact of service variants, and present a strategy for switching variants at runtime.
翻译:边缘计算的共同部署模式基于(可兼容的)向云端倾卸下来的微服务。运行时间调整通常基于粗粗和昂贵的管理操作,如资源重新配置或迁移等。但是,服务本身仍然是不适应的,恶化了与云型计算相比,大电子计算本已有限的弹性。边缘计算应用程序往往对执行时间有严格的要求,但在计算质量方面则具有灵活性。利用这一交易的潜在好处仍然有待开发。本文介绍了适应性微观服务的概念,提供特定功能的替代变体。我们定义了服务所谓的服务变体,这些变体表现为不同的算法、参数和辅助数据。这些变体允许对QOS(例如,最可耐性执行时间)和计算质量进行微量交易。我们把适应性微观服务变型的变式纳入一个实用变式的变式战略框架。我们将当前变式的变式服务变换了Edge电子算法,展示了实际变式的变式框架。