Bené：边缘按需经济高效的扩展
Bené: On Demand Cost-Effective Scaling at the Edge
摘要：
边缘计算在许多领域和企业中变得越来越流行。然而，给定边缘的局部约束（即，只有附近的边缘是有用的），复用不同的工作负载变得具有挑战性。这导致为峰值需求提供的边缘资源的资源利用率很低。允许多路复用的一种简单方法是通过微型数据中心，使计算接近用户，同时支持整个数据中的各种工作负载以及边缘。在本文中，我们主张采用企业内部专用边缘资源和跨实体共享的微型数据中心中的按需资源的混合方法。我们表明，这种混合方法是一种有效且具有成本效益的方法，可以扩展工作负载，并消除每个企业过度配置专用资源的需求。此外，与仅使用跨企业边缘的扩展方法相比，微型数据中心还形成了可信赖的第三方，可以维护重要的服务质量保证，如数据隐私，安全性和可用性。
英文摘要：
Edge computing has become increasingly popular across many domains and enterprises. However, given the locality constraint of edges (i.e., only close-by edges are useful), multiplexing diverse workloads becomes challenging. This results in poor resource utilization in edge resources that are provisioned for peak demand. A simple way to allow multiplexing is through micro-data centers, that bring computation close to the users while supporting diverse workloads throughout the data, along with edges. In this paper, we argue for a hybrid approach of dedicated edge resources within an enterprise and on demand resources in micro-data centers that are shared across entities. We show that this hybrid approach is an effective and cost-efficient way for scaling workloads and removes the need for over-provisioning dedicated resources per enterprise. Moreover, compared to a scaling approach that uses only the edges across enterprises, micro-data centers also form a trusted third party that can maintain important quality of service guarantees such as data privacy, security, and availability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
