CRII: NeTS: Scaling Distributed Storage with Programmable Switches

CRII：NeTS：使用可编程交换机扩展分布式存储

• 批准号: 1755646
• 负责人: Xin Jin
• 金额: $ 17.43万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1755646&HistoricalAwards=false
• 关键词: CRII; NeTS; Scaling; Distributed; Storage

Modern Internet services, such as search, social networking and e-commerce, depend critically on high performance distributed storage. As these services scale to billions of users, system operators are increasingly relying on in-memory storage to meet the necessary throughput and latency demands. A major challenge in scaling distributed storage is coping with skewed, dynamic workloads, which can lead to severe load imbalance and performance degradations. While traditional flash-based and disk-based storage can be balanced using a fast in-memory caching layer, server-based caching does not work for in-memory storage, because there is little difference in performance between the caching and storage layers. This project investigates a new distributed storage architecture that leverages the power and flexibility of new generation programmable switches to cache data in the network. The project goal is to not only improve the performance and reliability of cloud systems in practice, but also provide new architectural and theoretical insights on classical distributed systems topics. This project will foster the collaboration between the networking and systems communities in the new area of co-designing networks and systems with programmable switches.The project will develop a new architecture to provide high aggregate throughput and low latency even under highly-skewed and rapidly-changing workloads. There are two major technical thrusts. The first one is to design the switch cache with limited switch functionalities and resources. The approach will be to exploit the match-action tables, register arrays, and multi-pipeline, multi-stage structure of modern switch designs to efficiently index and pack variable-length objects into limited switch table and memory resources. The second research thrust is to design the overall system to achieve scalability, consistency and fault-tolerance. While these are classical distributed systems topics, they will be revisited in a new type of heterogeneous system which consists of fast switch caches and general-purpose storage servers. A prototype system will be constructed using both programmable software and hardware switches, and extensively evaluated with a wide range of realistic and synthetic workloads.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.

搜索、社交网络和电子商务等现代互联网服务严重依赖于高性能分布式存储。随着这些服务扩展到数十亿用户，系统运营商越来越依赖内存存储来满足必要的吞吐量和延迟需求。扩展分布式存储的一个主要挑战是处理倾斜的动态工作负载，这可能导致严重的负载不平衡和性能下降。虽然传统的基于闪存和基于磁盘的存储可以使用快速内存缓存层来平衡，但基于服务器的缓存不适用于内存存储，因为缓存层和存储层之间的性能差异很小。该项目研究了一种新的分布式存储架构，该架构利用新一代可编程交换机的功能和灵活性来缓存网络中的数据。该项目的目标不仅是在实践中提高云系统的性能和可靠性，而且还为经典分布式系统主题提供新的架构和理论见解。该项目将促进网络和系统社区之间的合作，共同设计具有可编程交换机的网络和系统。该项目将开发一种新的架构，即使在高度倾斜和快速变化的工作负载下也能提供高聚合吞吐量和低延迟。有两个主要的技术推动力。第一种是在交换机功能和资源有限的情况下设计交换机缓存。该方法将利用匹配动作表，寄存器阵列，和多流水线，多级结构的现代交换机设计，有效地索引和包装成有限的交换机表和内存资源的可变长度的对象。第二个研究重点是设计整个系统，以实现可扩展性，一致性和容错性。虽然这些都是经典的分布式系统的主题，他们将在一种新型的异构系统，其中包括快速切换缓存和通用存储服务器重新访问。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值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

Harmonia: Near-Linear Scalability for Replicated Storage with In-Network Conflict Detection

• DOI: 10.14778/3368289.3368301
• 发表时间: 2019-04
• 期刊: Proc. VLDB Endow.
• 作者: Hang Zhu;Zhihao Bai;Jialin Li;Ellis Michael;Dan R. K. Ports;I. Stoica;Xin Jin

ASAP: Fast, Approximate Graph Pattern Mining at Scale

• 发表时间: 2018
• 作者: A. Iyer;Zaoxing Liu;Xin Jin;S. Venkataraman;V. Braverman;I. Stoica

Neural packet classification

• DOI: 10.1145/3341302.3342221
• 发表时间: 2019-02
• 期刊: Proceedings of the ACM Special Interest Group on Data Communication
• 作者: Eric Liang;Hang Zhu;Xin Jin;I. Stoica

AWStream: adaptive wide-area streaming analytics

• DOI: 10.1145/3230543.3230554
• 发表时间: 2018-08
• 期刊: Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication
• 作者: Ben Zhang;Xin Jin;Sylvia Ratnasamy;J. Wawrzynek;Edward A. Lee

QPipe: quantiles sketch fully in the data plane

• DOI: 10.1145/3359989.3365433
• 发表时间: 2019-12
• 期刊: Proceedings of the 15th International Conference on Emerging Networking Experiments And Technologies
• 作者: Nikita Ivkin;Zhuolong Yu;V. Braverman;Xin Jin