Self-healing of Radio Access Network Slices

Wang, Y., Feng, G., Wang, J., Wei, F., Sun, Y. and Qin, S. (2021) Self-healing of Radio Access Network Slices. In: 2021 IEEE International Conference on Communications (ICC 2021), 14-23 Jun 2021, ISBN 9781728171227 (doi: 10.1109/ICC42927.2021.9500408)

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Abstract

Radio Access Network (RAN) slicing is a promising architectural technology to address extremely diversified service demands for future mobile networks. As an essential requirement for RAN slicing, self-healing is to provide services with certain quality requirements by minimizing the impact of mobile network failings. In this paper, we propose a Multi-objective Pareto Optimization based Self-healing (MPOS) scheme to solve the SRANS problem. We model the SRANS problem as a multi-objective optimization problem with aim of maximizing the self-healing profits of individual RAN slices and demonstrate the NP-hardness. In proposed MPOS scheme, we employ self-conditioned GANs to replace the offspring reproduction module in the traditional Multi-Objective Evolutionary Algorithm (MOEA), where the insufficiency of diversity maintenance in MOEA is effectively overcome. Furthermore, we theoretically prove that MPOS framework is guaranteed to converge to the optimal Pareto solution set with probability 1. Numerical results demonstrate that our MPOS scheme is effective in reducing the inverted generational distance of optimal Pareto solutions and achieving high profit and isolation level of RAN slices.

Item Type:Conference Proceedings
Additional Information:This work was supported by the National Key Research and Development Program of China under Grant number 2020YFB1806804, the National Science Foundation of China under Grant number 62071091 and ZTE Industry-Academia-Research Cooperation Funds
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Sun, Dr Yao and Feng, Professor Gang
Authors: Wang, Y., Feng, G., Wang, J., Wei, F., Sun, Y., and Qin, S.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
ISSN:1938-1883
ISBN:9781728171227
Published Online:06 August 2021
Copyright Holders:Copyright © 2021 IEEE
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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