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

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.

云计算系统内的数据存储依赖于将数据副本存储在多个服务器上以获得可靠性的复制协议。复制协议的一个理想属性是强一致性-即使在某些服务器出现故障时，具有数据副本的多个服务器也能够作为具有一个数据副本的单个高性能系统。现有的强一致性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。本项目旨在探索现有协议的低效率，并为云计算系统设计新的协议。本项目将研究现有复制协议的资源效率，重点关注资源共享环境下的云部署。如果不考虑其他环境因素，如编程语言和框架选择，这种调查将是不完整的。此外，该项目将利用调查结果设计新的资源高效协议和优化。这些将利用核心算法的改进以及新的硬件技术，如远程直接存储器访问（RDMA）和非易失性存储器（NVM）。开发的协议将简化通信，避免不必要的消息交换，优先考虑较低的开销通信策略，并减少工作amplification.Educational和技术转让方面发挥了重要作用，在这个项目。这项工作将通过会议和合作促进学术界和工业界之间的双向技术转让。为了进一步消除技术转移障碍，所有协议和算法都将得到充分的记录和开源。该项目将使人们关注在云计算环境中构建资源高效软件的重要性，并将开发一个新的课程，项目和实验室模块，强调设计技术和编程实践，提高云软件的资源效率。通过课程和教学，该项目旨在吸引本科生和来自代表性不足群体的学生。该项目将在GitHub平台上发布所有代码工件，数据和课程材料。如适用，任何大型数据集或原始数据材料将存储在公共云存储系统中。该项目将维护GitHub存储库，可在https://github.com/resource-efficient-replication上获得。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。