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

George Washington University, Washington DC

Investigators

Abstract

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.