Edge computing allows for the decentralization of computing resources. This decentralization is achieved through implementing microservice architectures, which require low latencies to meet stringent service level agreements (SLA) such as performance, reliability, and availability metrics. While cloud computing offers the large data storage and computation resources necessary to handle peak demands, a hybrid cloud and edge environment is required to ensure SLA compliance. Several auto-scaling algorithms have been proposed to try to achieve these compliance challenges, but they suffer from performance issues and configuration complexity. This chapter provides a brief overview of edge computing architecture, its uses, benefits, and challenges for resource scaling. We then introduce Service Level Agreements, and existing research on devising algorithms used in edge computing environments to meet these agreements, along with their benefits and drawbacks.

翻译：边缘计算实现了计算资源的去中心化。这种去中心化通过微服务架构实现，该架构需要低延迟以满足严格的性能、可靠性和可用性等服务水平协议（SLA）指标。虽然云计算提供了处理峰值需求所需的大规模数据存储和计算资源，但需要混合云与边缘环境来确保SLA合规性。已有多种自动扩缩容算法被提出以应对这些合规性挑战，但它们存在性能问题和配置复杂性。本章简要概述边缘计算架构、其用途、优势以及资源扩缩面临的挑战。随后介绍服务水平协议，以及现有关于设计用于满足这些协议的边缘计算环境算法的研究，并分析其优缺点。