AI-Based E2E Resilient and Proactive Resource Management in Slice-Enabled 6G Networks

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-01-10 DOI:10.1109/TNSE.2025.3528190

Ali Nouruzi;Nader Mokari;Paeiz Azmi;Eduard A. Jorswieck;Melike Erol-Kantarci

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引用次数: 0

Abstract

Intelligence and flexibility are the two main requirements for next-generation networks that can be implemented in network slicing (NetS) technology. This intelligence and flexibility can have different indicators in networks, such as proactivity and resilience. In this paper, we propose a novel proactive end-to-end (E2E) resource management in a packet-based model, supporting NetS. Since guaranteeing quality of service (QoS) in NetS has many challenges, we present an intelligent method that has two characteristics: resilience and proactivity. Guaranteeing successful slice provision is costly, we formulate a comprehensive model of the imposed costs. To minimize the cost function, we introduce a new optimization problem with radio, processing, and transmission resource constraints. In addition, we introduce two new constraints that guarantee the proactivity and resilience capabilities of the network based on the probability of successful slice provisioning (PSSP). Since the proposed optimization problem is non-convex, online and belongs to the NP-hard category, we adopt a deep reinforcement learning (DRL) based method to solve it. In particular, the soft actor critic (SAC) method is utilized due to its robustness in uncertain environment that the obtained results reveal that the applied method can improve the percentage of successful slice provisioned (PrSSP). In addition, the resiliency time is reduced comparatively. Finally, as the main achievement, the resilient scenario improves PrSSP compared to the non-resilient scenario.

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基于人工智能的片式 6G 网络 E2E 弹性和主动资源管理

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.