NeTS: Medium: SLATE: Service Layer Traffic Engineering

大多数人每天都在他们的手机和笔记本电脑上使用在线应用程序——网站、地图、视频会议、购物、短信等等。这些应用程序托管在云中，这意味着它们的应用程序逻辑、数据库和存储的重要部分在大型数据中心的服务器上运行，通常在全国或世界各地的多个站点上运行。这类应用程序通常包含许多不同的软件组件，它们在幕后执行数十或数百个小任务，以共同产生用户想要的结果，比如网页或高质量的视频流。由于这些云托管应用程序的复杂性以及它们从用户接收到的不可预测的工作负载，因此很难优化它们的性能和资源使用。目前的典型结果是，应用程序的资源供应过剩——这意味着，它们被分配的计算资源远远超过了所需的资源；70%甚至更多的浪费是很常见的。当前处理此问题的方法试图规划更好的长期资源分配，但不能帮助解决短期工作负载变化，也不能帮助解决与网络相关的成本问题。该项目将设计和开发一个称为服务层流量工程（SLATE）的系统。SLATE将帮助云托管应用程序优化任务性能，以更少的资源浪费优雅地处理短期工作负载波动，并优化云带宽和计算成本。在技术层面上，SLATE将为现代云托管应用程序提供易于使用的优化，并在应用程序下面添加一个新的优化层。SLATE关注的是基于微服务的应用程序：这种应用程序将每个任务分成许多小组件，这些组件运行在不同的服务器上。SLATE将扩展现有的开源服务网格，这些服务网格目前为基于微服务的应用程序提供网络功能。然而，这涉及重大的新挑战。首先，该项目将开发一种技术，在跨越多种资源类型（计算和网络容量）的瓶颈时自动确定请求的优先级。其次，该项目将设计在可能的服务器之间实时路由请求的方法，在多集群环境中智能地权衡延迟、成本、带宽和异常值。第三，该项目将开发一种基于理论的方法，将服务层流量工程问题分解为一个分散的设计，其中局部决策可以实现快速反应，而足够的全局协调可以实现最优性。该项目将通过显著的性能、资源利用率和成本改进，使云托管应用程序受益，从而实现更广泛的影响。该项目还将支持扩大计算机参与的活动，包括指导本科生研究经验（REU）学生，吸引代表性不足的群体的申请人，以及参加EECS新星研讨会。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Most people use online applications -- web sites, maps, videoconferencing, shopping, messaging, and more -- on their phones and laptops every day. These applications are hosted in clouds, meaning that important parts of their application logic, databases, and storage run on servers in large data centers, typically in multiple sites across the country or world. Such applications usually involve many distinct components of software performing dozens or hundreds of small tasks behind the scenes to collectively produce the result the user wants, like a web page or a high-quality video stream. Because of the complexity of these cloud-hosted applications and the unpredictable workload they receive from users, it is difficult to optimize their performance and resource usage. The typical result today is that applications' resources are overprovisioned -- meaning, they are allocated much more computing resources than necessary; 70% waste, or even more, is common. Current methods to deal with this problem try to plan better long-term resource allocations, but do not help with short-term workload changes and do not help with network-related costs.This project will design and develop a system called Service Layer Traffic Engineering (SLATE). SLATE will help cloud-hosted applications to optimize the performance of tasks, deal gracefully with short-term workload fluctuations with less resource waste, and optimize cloud bandwidth and computing costs. At a technical level, SLATE will provide easily usable optimization for modern cloud-hosted applications with a new optimization layer beneath the application. SLATE focuses on applications which are microservice-based: such applications split each task into many small components which run on different servers. SLATE will extend existing open-source service meshes, which today provide networking functionality for microservice-based applications. However, this involves significant new challenges. First, the project will develop techniques to prioritize requests automatically across bottlenecks spanning multiple resource types (computing and network capacity). Second, the project will design methods to route requests in real time among possible servers, intelligently trading off latency, cost, bandwidth, and outlier considerations in multi-cluster environments. Third, the project will develop a theoretically grounded approach to decompose the service layer traffic engineering problem into a decentralized design, with local decisions enabling fast reaction, and just enough global coordination to achieve optimality.The project will seek to achieve substantial broader impact by benefiting cloud-hosted applications with significant performance, resource utilization, and cost improvements. The project will also support activities to broaden participation in computing, including mentoring Research Experiences for Undergraduates (REU) students, attracting applicants from underrepresented groups, and participating in the EECS Rising Stars workshops.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.