NeTS: Small: Collaborative Research: Ultrascale WDM-based Datacenter Networks: Architecture Design and Control Algorithms

庞大的数据中心日益成为互联网的核心。本项目将为数据中心开发一种基于光纤的网络架构，以及相关的网络控制算法，该架构具有高度可配置性、可扩展性，满足未来数据中心的需求。所提出的架构是分层的，在最低层次使用低成本的无源光学，在更高层次使用电子和可配置光交换的组合，从而在光学系统和器件的成本和能力之间取得平衡。此外，无源光学的使用显著降低了能耗，这已成为大型数据中心的一个重要考虑因素。我们的研究计划包括架构开发和算法设计，包括：1。开发一种低成本、可扩展、可配置的基于波分复用（WDM）的DCN架构，以满足未来数据中心的通信需求。2 .开发动态重配置算法，根据流量条件的变化改变网络拓扑结构，以减少网络上的通信负荷。调查被动光学的使用，以减少能源消耗，并在能源消耗方面比较不同的建筑替代方案。所提出的架构有可能极大地改变dcn的设计方式，显著提高其可扩展性、稳健性和能源效率。此外，这项调查将包括：(1)通过期刊和会议出版物传播结果，以推进该领域；(2)将通过这项工作开发的新理论和算法纳入高级研究生课程；(3)本科生实验项目的开发；(4)向行业转移技术（包括行业合作伙伴的潜在早期采用）和(5)培训研究生和本科生。

Huge data centers increasingly form the heart of the Internet. This project will develop an optical-fiber-based network architecture for data centers, together with associated network control algorithms, that is highly configurable, scalable, and meets the requirements of future data centers. The proposed architecture is hierarchical and uses low-cost passive optics at the lowest levels of the hierarchy, and a combination of electronic and configurable optical switching at higher layers, thus striking a balance between cost and capability of optical systems and devices. Moreover, the use of passive optics significantly reduces energy consumption, which has become an important consideration in large data centers. Our research plan includes both architecture development and algorithm design, including:1. Develop a Wave-Division-Multiplexing (WDM)-based DCN architecture that is low-cost, scalable, and configurable, for meeting the communication requirements of future data centers.2. Develop dynamic reconfiguration algorithms for changing the network topology in response to changes in traffic conditions, in order to reduce the communication load on the network.3. Investigate the use of passive optics in order to reduce energy consumption, and compare different architectural alternatives in terms of energy consumption.The proposed architecture has the potential to dramatically change the way that DCNs are designed, significantly improving their scalability, robustness and energy efficiency. In addition, this investigation will include: (1) dissemination of the results through journal and conference publications to advance the field; (2) incorporation of new theory and algorithms developed through this work into advanced graduate classes; (3) development of experimental projects for undergraduate students; (4) technology transfer to industry (including potential early adoption by an industry partner) and (5) training of graduate and undergraduate students.