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CNS Core: Small:On Parallelizing Optical Network Design Problems:Towards Network Optimization as a Service

$439,148FY2019CSENSF

North Carolina State University, Raleigh NC

Investigators

Abstract

Planning, deploying, and engineering the networks that make up the Internet infrastructure involve complex problems generically referred to as "network design" problems. Effective and efficient solutions to network design problems are crucial to the operation and economics of the Internet and its ability to support critical and reliable education, government, commercial and science-related communication services. Network design gets increasingly difficult as networks grow larger. This research project aims to address this challenge by investigating new approaches for tackling network design problems for large networks in a scalable manner. This project aims to make contributions that will lead to a paradigm shift in efficient, scalable solutions to network design problems. The project approach will be to develop parallel solutions that are applicable to a wide range of problems by exploiting a feature common to all, namely, that the optimization process incorporates both a routing aspect and a resource allocation aspect. The research plan is to partition the solution space across the routing dimension into a set of mutually exclusive and collectively exhaustive subspaces, which may be explored in parallel as independent subproblems. Specifically, each subspace corresponds to a fixed routing path for each node pair, and the corresponding subproblem involves searching only for an optimal resource assignment along the given paths. Consequently, subproblems are independent of each other and may be solved in parallel by leveraging available cluster/cloud computing resources to speed up the overall execution time. The approach will look at intelligent ways to prune the set of subspaces that practically need to be explored. The algorithmic results of this project will be integrated into an open-source tool that will be made available to students, researchers, and practitioners. The research will lay the foundation for a future "Network Optimization as a Service (NOaaS)" model for network optimization to be delivered remotely and on demand as a cloud service. 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.

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