Collaborative Research: CNS Core: Small: Resource-efficient, Strongly Consistent Replication for the Cloud

合作研究：CNS 核心：小型：资源高效、强一致性的云复制

• 批准号: 2149443
• 负责人: Aleksey Charapko
• 金额: $ 24.96万
• 依托单位: University of New Hampshire
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2149443&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Small; Collaborative; Research; CNS; Core; Small

Data storage within cloud computing systems relies upon replication protocols that store copies of data on multiple servers for reliability. A desirable property of a replication protocol is strong consistency - the ability of multiple servers with copies of data to act as a single, highly performant system with one copy of the data, even when some of the servers fail. Existing strongly consistent protocols improve performance at the cost of sacrificing resource efficiency, which increases the cost of data storage on the cloud. This project aims to explore the inefficiencies in current protocols and design new protocols for cloud computing systems.This project will study the resource efficiency of existing replication protocols, focusing on cloud deployments in resource-shared settings. Such investigation would be incomplete without including other environmental factors, such as programming language and framework choices. In addition, the project will use the investigation results to design new resource-efficient protocols and optimizations. These will leverage the core algorithmic improvements in addition to new hardware technologies, such as Remote Direct Memory Access (RDMA) and Non-volatile Memory (NVM). The developed protocols will streamline communication, avoid unnecessary message exchange, prioritize lower overhead communication strategies, and reduce work amplification.Educational and technology transfer aspects play a significant role in this project. This work will facilitate bidirectional technology transfer between academia and industry through meetings and collaborations. To further remove technology-transfer barriers, all protocols and algorithms will be well-documented and open-sourced. This project will bring under the spotlight the importance of building resource-efficient software in cloud computing environments and will develop a new class, projects, and lab modules emphasizing design techniques and programming practices that increase resource efficiency in the cloud software. Through the curriculum and teaching, the project aims to engage undergraduate students and students from underrepresented groups.This project will release all code artifacts, data, and curriculum materials on the GitHub platform. If applicable, any large datasets or raw data materials will be stored in a public cloud storage system. The project will maintain the GitHub repository, available at https://github.com/resource-efficient-replication. Upon the completion of the project, the GitHub handle will remain active for historical purposes.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.

云计算系统中的数据存储依赖于复制协议，该协议存储在多个服务器上的数据副本以获得可靠性。复制协议的理想属性是强大的一致性 - 具有数据副本的多个服务器的能力，即使某些服务器失败，具有数据副本的单个高性能系统，即使是一个数据副本。现有的强烈一致的协议以牺牲资源效率为代价提高了性能，这增加了云上数据存储的成本。该项目旨在探索当前协议中的效率低下，并为云计算系统设计新协议。本项目将研究现有复制协议的资源效率，重点关注资源共享设置中的云部署。如果不包括其他环境因素，例如编程语言和框架选择，这种调查将是不完整的。此外，该项目将使用调查结果来设计新的资源有效协议和优化。除了新的硬件技术，例如远程直接内存访问（RDMA）和非挥发性内存（NVM），这些还将利用核心算法改进。开发的协议将简化沟通，避免不必要的消息交换，优先考虑较低的间接费用沟通策略并减少工作放大。教育和技术转移方面在该项目中起着重要作用。这项工作将通过会议和合作促进学术界和行业之间的双向技术转移。为了进一步消除技术传输障碍，所有协议和算法都将得到充分记录和开源。该项目将成为众所周知的云计算环境中构建资源效率软件的重要性，并将开发一个新的类，项目和实验室模块，强调设计技术和编程实践，从而提高云软件中资源效率。通过课程和教学，该项目旨在吸引来自代表性不足的小组的本科生和学生。该项目将在GitHub平台上发布所有代码文物，数据和课程材料。如果适用，任何大型数据集或原始数据材料都将存储在公共云存储系统中。该项目将维护GITHUB存储库，请访问https://github.com/Resource-fellicic-replication。该项目完成后，GitHub手柄将保持活跃，以实现历史目的。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来评估值得支持的。