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

现代互联网服务旨在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。这样的布置强加了对存储系统的读取和写入请求的响应时间与数据存储/传输成本之间的基本权衡。现有的分布式存储解决方案解决这一权衡可能会导致次优的结果。首先，如今要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，在这两者之间几乎没有选择。此外，许多理论上可行的折衷点目前在实践中无法实现。本研究项目旨在设计和构建一个分布式存储解决方案，提供一个单一的设计，以实现广泛的可行的延迟-成本权衡。本项目的首要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-成本权衡，以及（2）实现了理论上可行的折衷空间的很大一部分，这是目前无法实现的。具体而言，该项目涉及克服以下关键挑战：（1）对低延迟和低成本的无缝支持;（2）确保跨广泛变化的网络延迟域和对象大小的高性能;以及（3）有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进行选择，而无需重新设计其服务。通过使云服务提供商可以访问更广泛的权衡空间区域，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以实现新的、低成本的、地理分布的服务和交互式协作应用。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，并在他们教授的课程中利用该项目的成果。将通过研究实习促进本科生的研究接触。研究人员计划建立在几个已经建立的推广活动，以帮助提高学生群体在计算机科学的多样性。从研究项目的结果，包括软件，将提供在：github.com/cns1901410.This奖反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。

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.