XPS: FULL: Collaborative Research: Enabling Scalable Cloud And Edge-device Integration Using Cross-layer Parallelism

XPS：完整：协作研究：使用跨层并行性实现可扩展的云和边缘设备集成

• 批准号: 1628991
• 负责人: Zhuoqing Mao
• 金额: $ 57.8万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1628991&HistoricalAwards=false
• 关键词: XPS; FULL; Collaborative; Research; Enabling

The importance of energy efficiency today is felt across all domains of computing. In particular, personal computing platforms are becoming increasingly wireless and miniaturized, but limited by trade-offs between battery lifetimes and computational requirements. Developing energy-efficient solutions is critical to the survival of the semiconductor industry. This project seeks to develop new abstractions to effectively utilize network and cloud resources to enable a scalable and energy-efficient mobile computing paradigm. The proposed hierarchical cloud computing architecture with cross-layer parallelism provides innovation for teaching networking, system, and architecture courses. It provides a platform to engage undergraduate students and community service agencies. Finally, this project is expected to have a high impact on global societies and economies.The proposed distributed system architecture leverages cross-layer parallelism to enable scalable, adaptive, and intelligent integration between edge mobile devices and clouds by intelligently partitioning and replicating computation between mobile devices and the cloud. This project redefines two classes of programming abstractions that enable seamless usage of: (1) network resources at transport layers and (2) any form of cloud resources whether local or remote. The proposed architecture strategically leverages network-level parallelism that transparently utilizes multiple network paths, in-network cloudlets that offer highly customized accelerators for offloaded computation, and remote cloud servers with more plentiful resources. These three components work in a coordinated way with awareness of the dynamic communication overhead, thereby ensuring scalability and energy efficiency of supporting both compute and network intensive distributed applications on mobile platforms.

如今，所有计算领域都感受到了能源效率的重要性。 特别是，个人计算平台正变得越来越无线化和小型化，但受到电池寿命和计算要求之间权衡的限制。开发节能解决方案对于半导体行业的生存至关重要。该项目旨在开发新的抽象，以有效利用网络和云资源，以实现可扩展且节能的移动计算范例。 所提出的具有跨层并行性的分层云计算架构为网络、系统和架构课程的教学提供了创新。它提供了一个吸引本科生和社区服务机构参与的平台。最后，该项目预计将对全球社会和经济产生重大影响。所提出的分布式系统架构利用跨层并行性，通过在移动设备之间智能分区和复制计算，实现边缘移动设备和云之间的可扩展、自适应和智能集成。设备和云。 该项目重新定义了两类编程抽象，可以无缝使用：(1) 传输层的网络资源；(2) 任何形式的云资源，无论是本地还是远程。 所提出的架构战略性地利用了网络级并行性，透明地利用多个网络路径、为卸载计算提供高度定制加速器的网络内云，以及具有更丰富资源的远程云服务器。这三个组件以协调的方式工作，并了解动态通信开销，从而确保支持移动平台上的计算和网络密集型分布式应用程序的可扩展性和能源效率。