CAREER: Towards Inter-Datacenter Communication for Next-Generation Networks

职业：迈向下一代网络的数据中心间通信

• 批准号: 1053757
• 负责人: Hakim Weatherspoon
• 金额: $ 60.01万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1053757&HistoricalAwards=false
• 关键词: CAREER; Towards; Inter; Datacenter; Communication

High-bandwidth, semi-private optical lambda networks carry growing volumes of data on behalf of large datacenters, both in cloud computing environments and for scientific, financial, defense, and other enterprises. These networks are treated as if they are perfect. However, it is not uncommon for them to suffer from unexpected performance degradations and loss rates, even when traffic is well-below capacity. This project studies end-to-end characteristics of lambda networks running at high speeds over long distances, with an eye toward better understanding loss, latency variations, and degraded throughput. This understanding is necessary for the design and efficient use of next-generation lambda networks and to enable the transition to cloud computing.The research described in this project will focus on measuring, characterizing, modeling, and informing new network and protocol design for optical lambda networks. The educational activities will make aspects of network research more accessible to students; promote research initiative among undergraduate and graduate students, and leverage (interdisciplinary) collaborations between Cornell and Howard University, a historically black college and university (HBCU).Intellectual Merit: Fundamental science requires well controlled experiments and observation. The research described in this project will produce novel network measurement instruments, along with a body of experimental knowledge needed for building networks and protocols that exhibit high performance. The research agenda has three major components.- Further Development of the Software Defined Network Adapter (SDNA) that the PI has designed. SDNA provides precise and reproducible measurements of an optical lambda network. By achieving extremely high levels of precision, SDNA can shed light on the complexities of flows that traverse high-speed networks.- Use of SDNA to measure and characterize optical lambda networks. These measurements will help explain observed packet loss at low data rates and reveal new aspects of network behavior.- Research and deploy new network protocols that enhance end-to-end performance perceived by applications.New network protocols will allow application developers and datacenter operators to better take advantage of the capacity of the underlying optical networks.Broader Impacts: The education/outreach agenda is designed to foster an environment for developing a new generation of network researchers who will take a keen interest in hands-on experimentation. There are two major components:- Research opportunities for undergraduate and graduate students as well as faculty during the summer and in a semester-long class. This will include exploring the design of hardware and software layers for an SDNA apparatus and using SDNA to conduct network research and analyze network measurements.- A partnership with Howard University (an HBCU) to collaborate on network research and inspire the next generation of underrepresented minority researchers.

高带宽、半专用光纤波长网络代表大型数据中心承载不断增长的数据量，无论是在云计算环境中，还是在科学、金融、国防和其他企业中。这些网络被视为完美无缺。然而，它们遭受意外的性能降级和丢失率的情况并不少见，即使在流量远远低于容量时也是如此。该项目研究远距离高速运行的lambda网络的端到端特性，着眼于更好地了解损耗、延迟变化和降低的吞吐量。了解这一点对于下一代波长网络的设计和高效使用以及向云计算的过渡是必要的。本项目中描述的研究将集中在测量、表征、建模和为光波长网络的新网络和协议设计提供信息。教育活动将使学生更容易接触到网络研究的各个方面；促进本科生和研究生的研究积极性，并利用康奈尔大学和霍华德大学(HBCU)之间的(跨学科)合作。智力优势：基础科学需要良好控制的实验和观察。本项目中描述的研究将产生新的网络测量仪器，以及构建表现出高性能的网络和协议所需的大量实验知识。研究议程有三个主要部分。-进一步开发PI设计的软件定义网络适配器(SDNA)。SDNA提供了对光波长网络的精确和可重复性的测量。通过实现极高的精确度，sDNA可以揭示穿过高速网络的流的复杂性。-使用sDNA来测量和表征光纤波长网络。这些测量将有助于解释在低数据速率下观察到的分组丢失，并揭示网络行为的新方面。-研究和部署新的网络协议，以增强应用程序感知的端到端性能。新的网络协议将使应用程序开发商和数据中心运营商能够更好地利用底层光纤网络的容量。广泛影响：教育/推广议程旨在为开发将对实践实验产生浓厚兴趣的新一代网络研究人员创造环境。它有两个主要组成部分：-为本科生和研究生以及教职员工在暑期和长达一学期的课程中提供研究机会。这将包括探索sDNA设备的硬件和软件层的设计，并使用sDNA进行网络研究和分析网络测量。-与霍华德大学(HBCU)合作，在网络研究方面进行合作，并激励下一代代表不足的少数族裔研究人员。