CAREER: Safe and Efficient Extensions for Low-Latency Multitenant Storage

职业：低延迟多租户存储的安全高效扩展

• 批准号: 1750558
• 负责人: Ryan Stutsman
• 金额: $ 55万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1750558&HistoricalAwards=false
• 关键词: CAREER; Safe; Efficient; Extensions; Low

Businesses are moving data and applications into the cloud, meaning that many applications and data are consolidated efficiently in one place on fewer servers. Cloud storage services must keep the data of thousands of customers separated while also allowing customers to operate on it efficiently. Safely intermixing customer-provided operations over data is problematic. Historically, processor hardware isolates programs, but increasing data access rates make that costly. This project develops a new approach to storage that allows safe operation on data without hardware protection using recent advances in programming languages.The approach combats data movement between disaggregated storage and compute nodes by having untrusted tenant extensions pushed to Sandstorm, a new cloud storage system. Sandstorm's insight is that storage extensions can use language-level isolation to eliminate hardware isolation overheads that cannot be avoided today: not with virtual machines, containers, nor serverless Lambdas. Sandstorm also eliminates copying data for safety, so extensions benefit from low-level hardware functionality like zero-copy network transmission. The project will develop multitenant benchmarks, low-cost performance-isolated concurrency mechanisms for multicores, techniques to minimize data movement within servers, storage extensions that demonstrate the benefits, and distributed extensions over clusters.As power limits data center scale, minimizing data movement out of storage becomes crucial. Sandstorm enables any cloud developer to accelerate data-intensive applications like real-time social network and natural graph analysis and fine-grained coordination of hundreds of thousands of autonomous vehicles. All artifacts will be developed openly under a permissive MIT license for academic and industrial use. The project includes development of a new education platform for teaching students about distributed systems and cloud computing at the graduate, undergraduate, and high school levels with a set of serverless computing labs targeted toward University of Utah students and summer camp attendees. All data, code, experiments, and benchmarks will be open and made publicly available through http://github.com/utah-scs/ and at http://utah.systems/ and retained for a minimum of three years beyond the project award period. All data, code, benchmarks, and experiments associated with all published results will also be hosted at http://dataverse.harvard.edu/dataverse/utah-scs as part of the Harvard Dataverse for long-term retention.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.

企业正在将数据和应用程序迁移到云中，这意味着许多应用程序和数据可以在更少的服务器上有效地整合到一处。云存储服务必须将数千个客户的数据分开，同时还允许客户高效地对其进行操作。在数据上安全地混合客户提供的操作是有问题的。从历史上看，处理器硬件会隔离程序，但不断提高的数据访问率会导致成本高昂。该项目开发了一种新的存储方法，允许使用编程语言的最新进展在没有硬件保护的情况下安全地操作数据。该方法通过将不受信任的租户扩展推送到新的云存储系统 Sandstorm 来阻止分解存储和计算节点之间的数据移动。 Sandstorm 的见解是，存储扩展可以使用语言级隔离来消除当今无法避免的硬件隔离开销：不能使用虚拟机、容器或无服务器 Lambda。为了安全起见，Sandstorm 还消除了数据复制，因此扩展受益于零复制网络传输等低级硬件功能。该项目将开发多租户基准、用于多核的低成本性能隔离并发机制、最大限度地减少服务器内数据移动的技术、展示其优势的存储扩展以及集群上的分布式扩展。由于功率限制了数据中心的规模，因此最大限度地减少数据移出存储变得至关重要。 Sandstorm 使任何云开发人员能够加速数据密集型应用程序，例如实时社交网络和自然图形分析以及数十万辆自动驾驶车辆的细粒度协调。所有工件都将在麻省理工学院的许可下公开开发，用于学术和工业用途。该项目包括开发一个新的教育平台，在研究生、本科生和高中阶段向学生教授分布式系统和云计算知识，并针对犹他大学的学生和夏令营参加者建立一组无服务器计算实验室。所有数据、代码、实验和基准都将通过 http://github.com/utah-scs/ 和 http://utah.systems/ 公开并在项目结束后保留​​至少三年颁奖期。与所有已发布结果相关的所有数据、代码、基准测试和实验也将托管在 http://dataverse.harvard.edu/dataverse/utah-scs，作为哈佛数据宇宙的一部分进行长期保留。该奖项反映了 NSF法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Narrowing the Gap Between Serverless and its State with Storage Functions

通过存储功能缩小 Serverless 与其状态之间的差距

• DOI: 10.1145/3357223.3362723
• 发表时间: 2019-11-20
• 期刊: Proceedings of the ACM Symposium on Cloud Computing
• 作者: Tian Zhang;Dong Xie;Feifei Li;Ryan Stutsman
• 通讯作者: Ryan Stutsman

Achieving high throughput and elasticity in a larger-than-memory store

在大于内存的存储中实现高吞吐量和弹性

• DOI: 10.14778/3457390.3457406
• 发表时间: 2021-04
• 期刊: Proceedings of the VLDB Endowment
• 影响因子: 2.5
• 作者: Kulkarni, Chinmay;Chandramouli, Badrish;Stutsman, Ryan
• 通讯作者: Stutsman, Ryan

On the Impact of Isolation Costs on Locality-aware Cloud Scheduling

隔离成本对本地感知云调度的影响

• DOI: 10.1109/infocom48880.2022.9796848
• 发表时间: 2024-09-14
• 期刊: ArXiv
• 作者: Ankit Bhardwaj;Meghana Gupta;Ryan Stutsman
• 通讯作者: Ryan Stutsman

XRP: In-Kernel Storage Functions with eBPF

XRP：带有 eBPF 的内核存储功能

• DOI: 10.1109/cluster51413.2022.00016
• 发表时间: 2024-09-14
• 期刊: 2022 IEEE International Conference on Cluster Computing (CLUSTER)
• 作者: Yuhong Zhong;Hao Li;Y. Wu;Ioannis Zarkadas;Jeffrey Tao;Evan Mesterhazy;Michael Makris;Junfeng Yang;Amy Tai;Ryan Stutsman;Asaf Cidon
• 通讯作者: Asaf Cidon

NrOS: Effective Replication and Sharing in an Operating System

NrOS：操作系统中的有效复制和共享

• 发表时间: 2024-09-14
• 作者: Ankit Bhardwaj;C. Kulkarni;Reto Achermann;I. Calciu;Sanidhya Kashyap;Ryan Stutsman;Amy Tai;Gerd Zellweger
• 通讯作者: Gerd Zellweger