DESC:Type I: Sustainable Serverless Computing

云计算改变了我们的日常生活，使我们能够从连接互联网的平台（包括智能手机、数字健康设备、联网汽车和智能家居系统）按需访问强大的计算机系统资源。无服务器计算是一种新兴的范例，它使这些智能平台能够访问细粒度的功能级云微服务。该范例允许云计算服务提供商更有效地提供其计算资源，从而为开发人员和服务提供商节省成本。这反过来又有望使数字智能在我们的日常生活中更容易获得、负担得起和普及。然而，无服务器计算最大的突出挑战之一是支持功能级性能保证，同时最大限度地减少托管无服务器计算的云数据中心对环境的影响。云数据中心已经成为全球碳排放、废水产生和电力使用的主要贡献者，而无服务器计算将加剧这些对全球环境的压力。该项目将涉及变革性研究，以实现可持续的无服务器计算，并将以集成的方式解决三个主要重点：1)将进行无服务器计算的性能和可持续性建模，以捕获数据中心中无服务器工作流的性能，同时还首次描述支持无服务器计算的碳足迹和用水量，包括制造、运营、运输、用水和寿命终止退役的间接费用；2)将开发封装层增强功能，以解决无服务器计算的一些最大性能瓶颈，例如高启动延迟、低性能存储和容错性；同时最大限度地减少与无服务器计算相关的操作和隐含碳足迹；3)编排层增强将基于混合进化学习和多智能体强化学习来设计，以最大限度地减少无服务器计算对环境的影响，同时满足跨地理分布数据中心平台的性能目标。该项目与国家气候发现云（NDC-C）计划的目标一致，因为它涉及基于云的数据建模、分析和优化各种新兴的无服务器计算应用程序，包括来自多模态数据和气候建模的天气预测，有望推进气候相关研究。该项目还旨在从根本上实现更具可持续性的云计算基础设施，以支持NDC-C计划范围内的大规模气候科学和工程工作量，同时减少执行这些工作的云计算数据中心对环境的破坏性影响。对无服务器计算的性能和环境影响的特征和共同优化的强调将促进低成本云计算的扩散，使其更具成本效益和无缝集成到计算驱动的服务中，从而丰富我们的日常生活。劳动力发展是该项目的另一个重要影响，高中生、本科生和研究生将在高性能计算、优化理论和环境可持续性等多学科领域接受培训。与工业伙伴的密切合作还将确保及时传播研究成果，并将其整合到现实世界的可持续气候友好型计算计划中。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。

Cloud computing has transformed our everyday lives by enabling on-demand access to powerful computer system resources from Internet-connected platforms including smartphones, digital health devices, connected vehicles, and smart home systems. Serverless computing is an emerging paradigm that enables fine granularity function-level cloud microservices to be accessible by these smart platforms. The paradigm allows cloud computing service providers to more efficiently provision their compute resources, which translates into cost savings for both developers and service providers. This in turn is expected to make digital intelligence more accessible, affordable, and pervasive in our everyday lives. However, one of the biggest outstanding challenges with serverless computing is to support function-level performance guarantees while minimizing the environmental impact of cloud datacenters that host serverless computing. Cloud datacenters are already a major contributor to global carbon emissions, wastewater generation, and electricity use, and serverless computing will exacerbate these pressures on the global environment. This project will involve transformative research to realize sustainable serverless computing with three major thrusts that will be addressed in an integrated manner: 1) Performance and sustainability modeling for serverless computing will be conducted to capture the performance of serverless workflows in datacenters while also characterizing carbon footprint and water use for supporting serverless computing for the first time, including the overheads from manufacturing, operation, transportation, water-use, and end-of-life decommissioning; 2) Encapsulation layer enhancements will be developed to address some of the biggest performance bottlenecks with serverless computing, such as high startup latency, low performance storage, and fault tolerance; while simultaneously minimizing operational and embodied carbon footprint associated with serverless computing; and 3) Orchestration layer enhancements will be devised based on hybrid evolutionary-learning and multi-agent reinforcement learning to minimize the environmental impact of serverless computing while meeting performance goals across geographically-distributed datacenter platforms.This project is aligned with the goals of the National Discovery Cloud for Climate (NDC-C) program as it involves cloud-based data modeling, analysis, and optimization for a variety of emerging serverless computing applications, including weather predictions from multi-modal data and climate modeling, that promise to advance climate-related research. The project also aims to realize fundamentally more sustainable cloud computing infrastructures that can support large-scale climate science and engineering workloads in the scope of the NDC-C program while reducing the damaging environmental impacts of cloud computing datacenters that execute them. The emphasis on characterizing and co-optimizing the performance and environmental impacts of serverless computing will improve the proliferation of low-cost cloud computing, making it more cost-effective and seamless to integrate into computing-driven services that can enrich our everyday lives. Workforce development is another important broader impact of this project, with high school students, undergraduate and graduate students being trained in the multi-disciplinary domains of high-performance computing, optimization theory, and environmental sustainability. Close collaboration with industrial partners will also ensure timely dissemination and integration of research outcomes into real-world sustainable climate-friendly computing initiatives.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.