Robust function deployment against uncertain recovery time in different protection types with workload-dependent failure probability

Zhu, Mengfei; Oki, Eiji

doi:10.1016/j.comnet.2023.109826

Computer Networks

2023

DOI: 10.1016/j.comnet.2023.109826

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Robust function deployment against uncertain recovery time in different protection types with workload-dependent failure probability

Mengfei Zhu

Eiji Oki

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2024

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Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance

Ros,

Tam,

Song

et al. 2024

Electronics

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Network functions virtualization (NFV) has become the platform for decomposing the sequence of virtual network functions (VNFs), which can be grouped as a forwarding graph of service function chaining (SFC) to serve multi-service slice requirements. NFV-enabled SFC consists of several challenges in reaching the reliability and efficiency of key performance indicators (KPIs) in management and orchestration (MANO) decision-making control. The problem of SFC fault tolerance is one of the most critical challenges for provisioning service requests, and it needs resource availability. In this article, we proposed graph neural network (GNN)-based deep reinforcement learning (DRL) to enhance SFC fault tolerance (GRL-SFT), which targets the chain graph representation, long-term approximation, and self-organizing service orchestration for future massive Internet of Everything applications. We formulate the problem as the Markov decision process (MDP). DRL seeks to maximize the cumulative rewards by maximizing the service request acceptance ratios and minimizing the average completion delays. The proposed model solves the VNF management problem in a short time and configures the node allocation reliably for real-time restoration. Our simulation result demonstrates the effectiveness of the proposed scheme and indicates better performance in terms of total rewards, delays, acceptances, failures, and restoration ratios in different network topologies compared to reference schemes.

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Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance

Ros,

Tam,

Song

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

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Robust function deployment against uncertain recovery time in different protection types with workload-dependent failure probability

Cited by 1 publication

References 27 publications

Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance

Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance

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