CNS Core:Medium:Collaborative Research:Towards Enabling Optimal Performance-Cost Tradeoffs in Distributed Storage

现代互联网服务的目标是始终可用，并提供低延迟响应。通常，这是通过将数据存储在靠近最终用户的多个站点上来实现的。这样的安排在对存储系统的读和写请求的响应时间和数据存储/传输成本之间强加了基本的权衡。用于解决此权衡的现有分布式存储解决方案可能会导致不太理想的结果。首先，要在今天实现不同的性能与成本权衡，需要使用完全不同的解决方案，在两者之间几乎没有选择。此外，许多在理论上看起来可行的权衡取舍点目前在实践中是无法实现的。该研究项目旨在设计和构建一个分布式存储解决方案，该解决方案提供单一设计来实现各种可行的延迟-成本折衷。该项目的总体目标是设计下一代分布式存储解决方案(1)可以配置为实现可变数据的所有可行的性能-成本折衷，以及(2)实现目前无法实现的理论上可行的折衷空间的很大一部分。具体地说，该项目涉及克服以下关键挑战：(1)无缝支持低延迟和低成本；(2)确保跨变化很大的网络延迟域和对象大小的高性能；以及(3)高效地维护擦除编码数据的一致性。这将允许应用程序开发人员使用复制或擦除编码从权衡空间中的所有可行点中进行选择，而无需重新设计他们的服务。通过使云服务提供商能够访问更大范围的权衡空间，该项目将有助于降低最终用户的云存储价格。此外，降低可实现的延迟界限可实现交互和协作的新的、低成本、地理分布的服务和应用。研究人员将与行业合作伙伴合作，将该项目的成果应用于实践，并在他们教授的课堂上利用该项目的成果。将通过科研实习促进本科生的科研接触。研究人员计划在已经建立的几项推广活动的基础上，帮助提高计算机科学领域学生群体的多样性。研究项目的结果，包括软件，将在以下网站上公布：githeb.com/cns1901410。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。

Modern Internet services aim to be always available and provide low latency responses. Typically, this is achieved by storing data on multiple sites close to the end-users. Such an arrangement imposes a fundamental trade-off between response times for read and write requests to storage systems and data storage/transfer costs. Existing distributed storage solutions for addressing this trade-off may result in sub-optimal outcomes. First, realizing different performance-vs-cost trade-offs today requires using radically different solutions with little choice in between. Also, many trade-off points that appear theoretically feasible are currently unachievable in practice. This research project aims to design and build a distributed storage solution that offers a single design to realize a wide range of feasible latency-cost trade-offs.The overarching goal of this project is to design next-generation distributed storage solutions (1) that can be configured to achieve all feasible performance-cost trade-offs on mutable data, and (2) that enables a significant portion of the theoretically feasible trade-off space that is currently unachievable. Specifically, the project involves overcoming the following key challenges: (1) Seamless support for low latency and low cost; (2) Ensuring high performance across widely varying network latency domains and object sizes; and (3) Efficiently maintaining consistency in erasure-coded data. This will allow application developers to select from all feasible points in the trade-off space, using replication or erasure coding, without having to redesign their services.By making a broader region of the trade-off space accessible to cloud service providers, this project will help reduce the price of cloud storage for end users. Additionally, lowering achievable latency bounds enables new, low-cost, geo-distributed services and applications that are interactive and collaborative. The researchers will work with industry partners to apply the outcomes from this project in practice, and leverage the results from this project in classes they teach. Research exposure for undergraduate students will be promoted through research internships. The researchers plan to build upon several already-established outreach activities to help improve diversity of the student population in computer science.The results from the research project, including software, will be made available at: github.com/cns1901410.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.