CSR: Small: Scalable Coordination for Wide-Area Distributed Systems
CSR: Small: Scalable Coordination for Wide-Area Distributed Systems
批准号:
1527629
负责人:
Murat Demirbas
金额:
$49.96万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-10-01 至 2020-09-30
中文摘要
并发执行任务的可伸缩协调对于大规模分布式系统来说是一个具有挑战性的开放问题。对于需要很少或根本不需要通信的松散依赖的任务,简单的抽象(如屏障同步)就足以进行协调。然而,对于需要更紧密同步的大规模云计算和Web服务应用程序(如在线事务处理系统、分布式文件系统和图形处理应用程序),需要细粒度的复杂协调服务。尤其是随着电子商务、社交网络和物联网对大规模Web服务的需求日益增长,广域(即跨集群、跨数据中心和跨Internet)的任务协调变得更加重要,传统的分布式协调技术无法扩展到广域网络来支持这些新一代应用。集中式协调无法根据广域中增加的距离进行扩展,而分布式协调无法根据所涉及的节点数量进行扩展。这项研究项目声称,使用一种名为Maestro的新型混合设计,可以实现广域范围内分布式任务的可扩展协调。Maestro框架将解决以下研究问题:(1)完全集中和完全分散的解决方案对协调的限制是什么,混合分层方法的可扩展性优势是什么?(2)如何利用位置感知来实现跨广域的高性能?(3)如何利用分区感知来实现跨广域的一致性?Maestro框架将采用分层的锁代理架构,具有新颖的锁租赁机制和智能/自适应的锁迁移。这种组合允许灵活控制,并提供集中式和分散式两种方法的最佳选择。作为各自域的权威机构,代理在运行时学习和适应任务的访问模式,以提高锁的局部性,从而提高可扩展性,同时它们还具有自治性,允许以分散的方式启动和执行独立的任务。Maestro将提供优化,如在服务器被请求之前主动将锁租赁给服务器,锁迁移(更改锁的主站点分配),以及共享/部分锁租赁,以便在适当时有选择地允许分散协调和放松一致性。建议的Maestro框架将在两个流行的分布式应用领域进行评估:用于分布式协调的广域ZooKeeper和广域分布式元数据管理。Maestro将填补在紧密耦合的一致性关键型分布式应用程序的广域可扩展协调方面的一个重要空白,并将通过研究生和本科生水平的课程开发、通过组织学术研讨会、向K-12学生外展、招募少数群体以及向社区分发工具和软件来增强科学/技术理解,从而产生更广泛的影响。
英文摘要
Scalable coordination of concurrently executing tasks is a challenging open problem for large-scale distributed systems. For loosely dependent tasks that require little or no communication, simple abstractions such as barrier synchronization suffice for coordination. However, for large-scale cloud-computing and web-services applications that require tighter synchronization (such as online transaction processing systems, distributed file systems, and graph processing applications), a fine-grained complex coordination service is needed. Especially with increasing demand for large-scale web-services for e-commerce, social networking, and Internet of Things, the coordination of tasks over wide-area (i.e., across clusters, across datacenters, and across Internet) has recently gained greater importance.Traditional distributed coordination techniques fail to scale for wide-area networks to support these new generation applications. Centralized coordination fails to scale with respect to the increased distances in the wide-area, whereas distributed coordination fails to scale with respect to the number of nodes involved. This research project claims that it is possible to achieve scalable coordination of distributed tasks over wide-area using a novel hybrid design, called Maestro. The Maestro framework will address the following research questions: (1) What are the limits of fully-centralized and fully-decentralized solutions to coordination, and what are the scalability benefits of a hybrid hierarchical approach? (2) How can locality-awareness be utilized to achieve high-performance across wide-area? (3) How can partition-awareness be utilized to achieve consistency across wide-area? The Maestro framework will employ a hierarchical lock broker architecture with a novel lock-leasing mechanism and smart/adaptive lock migration. This combination allows flexibility of control and provides the best of both centralized and decentralized approaches. As the authority of their respective domains, the brokers learn and adapt to the access patterns of tasks at runtime to improve lock-locality and hence scalability, while they also have autonomy to allow independent tasks to be initiated and executed in a decentralized manner. Maestro will provide optimizations such as proactive leasing of locks to servers even before they are requested, lock migration (changing primary site assignment of locks), and shared/fractional lock-leasing to selectively allow decentralized coordination and relaxed consistency when appropriate.The proposed Maestro framework will be evaluated on two popular distributed application domains: wide-area ZooKeeper for distributed coordination, and wide-area distributed metadata management. Maestro will fill an important gap in the wide-area scalable coordination of tightly-coupled consistency-critical distributed applications, and it will enable further broader impacts through graduate and undergraduate level curriculum development, enhancing scientific/technological understanding via organizing academic workshops, outreaching to K-12 students, recruitment of minority groups, and distributing tools and software to the community.
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