NeTS: JUNO2: Resilience in Next-Generation Intelligent Optical Networks

由于其巨大的带宽，世界上的电信基础设施由光纤主导。为了支持处于商业和日常生活中心的互联网，已经并将继续在该基础设施上进行巨额投资。然而，随着带宽需求的增长，网络变得更加复杂，管理和防范自然灾害和其他灾难变得更加困难。因此，网络设计人员越来越多地转向由基本功能的简单构建块组成的光节点。该项目旨在使网络基础设施具备对故障的恢复力，无论是小规模的(由于组件或系统退化)还是大规模的(例如，由于灾难)。将制定从组件级别到网络级别再到服务级别的多个级别的复原力计划。这是与日本名古屋大学和香川大学的研究人员合作的项目。合作将利用该项目的日本合作者拥有的广泛的实验室设备来制作原型和测试所开发的技术，以及与行业的密切互动。该项目的成果将增加光网络的可信性，光网络是我们信息和通信基础设施的骨干。这项研究解决了在从组件级到网络级再到服务级的多个粒度上设计可信光网络的挑战性问题。将通过利用机器学习和马尔可夫决策过程等多种技术，开发具有成本效益的体系结构和实用而智能的算法，以便在多重故障中幸存下来，并提供服务级别可用性保证。我们的研究目标是：(A)通过以经济有效的方式引入冗余来设计由不可靠元件组成的高可靠的光节点。(B)在网络级别设计能够抵抗多种故障的智能算法。(C)设计可靠的服务资源管理算法。(D)开发一个小型节点原型，并在系统测试台上对其性能进行评估。这将利用该项目的日本伙伴机构的实验室设施来实现。这个项目将使新的理论和算法被纳入高级研究生班，并为本科生开发新的实验项目。该项目将招收来自代表性不足的少数族裔的学生，并包括广泛的K-12外展。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The world's telecommunication infrastructure is dominated by fiber optics because of its tremendous bandwidth. Huge investments have been and continue to be made in that infrastructure in order to support the Internet, which is at the center of business and daily life. As demand for bandwidth grows, however, the network becomes more complex and harder to manage and protect against natural and other disasters. Network designers are therefore increasingly turning toward optical nodes composed of simple building blocks of essential functions. This project aims to equip the network infrastructure with resilience against failures, both small-scale (due to component or system degradation) and large-scale (due to disasters, for example). Resilience schemes at multiple levels, ranging from component-level to network-level to service-level, will be developed. This is a collaborative project with researchers from Nagoya University and Kagawa University in Japan. The collaboration will leverage the extensive laboratory equipment for prototyping and testing the developed technology and the close interaction with industry that the project's Japanese collaborators have. The results of the project will increase the trustworthiness of optical networks, which form the backbone of our information and communications infrastructure. The research addresses challenging problems in designing trustworthy optical networks at multiple granularities ranging from component level to network level and to service level. Cost-efficient architectures and practical and intelligent algorithms for surviving multiple failures and for providing service-level availability guarantees will be developed by leveraging multiple techniques such as machine learning and Markov decision processes. Our research objectives are to:(a) Design highly reliable optical nodes that consist of unreliable components by introducing redundancy in a cost-effective manner.(b) Design intelligent algorithms for surviving multiple failures at the network level.(c) Design trustworthy service resource management algorithms.(d) Develop a small-scale node prototype and evaluate its performance in a system testbed. This will be achieved using the laboratory facilities at the project's Japanese partner institutions. This project will enable new theory and algorithms to be incorporated into advanced graduate classes and new experimental projects to be developed for undergraduate students. The project will recruit students from underrepresented minorities, and includes extensive K-12 outreach.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.