CRII: CNS: Towards Robust RAN Slicing: Theories, Algorithms, and Applications

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With the rapid growth of new services and Internet applications, traditional cellular networks are now faced with a major challenge of supporting diverse applications. To address the various application demands, Radio Access Network (RAN) slicing has become one of the most promising architectural technologies for the forthcoming 5G era. RAN slicing allows the physical infrastructure resources to be shared across many RAN slices, with each slice built on top of the underlying physical RAN (substrate) is a separate logical network, which provides a set of services. Each RAN slice is constituted by various virtual network functions (VNFs) distributed geographically in numerous substrate nodes. Failures may occasionally arise from substrate. RAN configuration schemes for the network are imperative to relieve VNFs from substrate node failures (remapping/re-embedding VNFs onto live substrate nodes). This project aims to explore a new scheme and algorithms to enhance the robustness of RAN slicing by addressing the RAN configuration issue for slice recovery in a unified framework, referred to as RS-configuration. This project will build a theoretical and computational scheme that formalizes this insight and provides efficient and practical techniques for RAN slice recovery by mapping VNFs efficiently in the RAN slicing. This research program will also be integrated with education to develop new courses and a new series of case-study class modules in an advanced networking course as well as the design and analysis of algorithm courses at Kennesaw State University. Outreach programs through the university will be utilized to ensure the dissemination of the results. The PI will also release the implementation of the proposed scheme and algorithms in public domains. The goal of this project is to develop optimization models and methods for 1) establishing the theoretical foundation for using RS-configuration to construct a VNF mapping plan for RAN slice recovery optimization; 2) developing a new scheme and algorithms needed to map VNFs efficiently and finally 3) applying our theoretical and algorithmic development to investigate the robustness of RAN slicing and trade-offs between RAN slice recovery and RAN configuration in the RAN-related networking environment. Methodologies will be developed in the context of mathematical programing and graph theory that will help obtain more efficient and fast solutions performing within reasonable bounds of computational complexity. Hence, this research on new scheme and algorithms for RAN slicing will provide the computational basis towards building a robust RAN slicing and contribute to the development of new networking technologies.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.