Edge computing seeks to enable applications with strict latency requirements by utilizing compute resources deployed closer to the users. The diverse, dynamic, and constrained nature of edge infrastructures necessitates a flexible orchestration framework that dynamically supports application QoS requirements. However, existing state-of-the-art orchestration platforms were designed for datacenter environments and make strict assumptions about underlying infrastructures that do not hold for edge computing. This work proposes a novel hierarchical orchestration framework specifically designed for supporting service operation over edge infrastructures. Through its novel federated cluster management, delegated task scheduling, and semantic overlay networking, our system can flexibly consolidate multiple infrastructure operators and absorb dynamic variations at the edge. We comprehensively evaluate our proof-of-concept implementation -- Oakestra -- against state-of-the-art solutions in both controlled and realistic testbeds and demonstrate the significant benefits of our approach as we achieve approximately 10x and 30% reduction in CPU and memory consumption, respectively.
翻译:边缘计算试图通过利用更接近用户的配置资源来启用严格延迟要求的应用。 边缘基础设施的多样性、动态性和受限性要求要求需要一个灵活管弦框架,能动态地支持应用QOS的要求。 但是,现有的最先进的管弦平台是为数据中心环境设计的,对不支持边端计算的基本基础设施作了严格的假设。 这项工作提出了一个新的等级管弦框架,专门用来支持边端基础设施的服务操作。 通过其新型的联合集束管理、授权任务安排和语义重叠网络,我们的系统可以灵活地整合多个基础设施运营商,吸收边缘的动态变化。 我们全面评估了我们受控和现实的测试床的测试测试测试的测试测试标准-Oakestra-与最先进的解决方案的实施,并展示了我们方法的重大效益,因为我们分别实现了大约10x和30%的CPU和记忆消耗量的削减。