Academic Journal
Hierarchical Placement Learning for Network Slice Provisioning
| Title: | Hierarchical Placement Learning for Network Slice Provisioning |
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| Authors: | Ajayi, Jesutofunmi, Di Maio, Antonio, Braun, Torsten |
| Source: | 2025 IEEE 50th Conference on Local Computer Networks (LCN). :1-9 |
| Publication Status: | Preprint |
| Publisher Information: | IEEE, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Networking and Internet Architecture |
| Description: | In this work, we aim to address the challenge of slice provisioning in edge-based mobile networks. We propose a solution that learns a service function chain placement policy for Network Slice Requests, to maximize the request acceptance rate, while minimizing the average node resource utilization. To do this, we consider a Hierarchical Multi-Armed Bandit problem and propose a two-level hierarchical bandit solution which aims to learn a scalable placement policy that optimizes the stated objectives in an online manner. Simulations on two real network topologies show that our proposed approach achieves 5% average node resource utilization while admitting over 25% more slice requests in certain scenarios, compared to baseline methods. Network Slicing, Multi-Objective Optimization, Online Learning, Edge Networks |
| Document Type: | Article Other literature type |
| DOI: | 10.1109/lcn65610.2025.11146290 |
| DOI: | 10.48620/91140 |
| DOI: | 10.48550/arxiv.2508.06432 |
| Access URL: | http://arxiv.org/abs/2508.06432 |
| Rights: | STM Policy #29 CC BY NC ND |
| Accession Number: | edsair.doi.dedup.....7ce5cfbbdb2d5c824416e32b2fa0265e |
| Database: | OpenAIRE |
| DOI: | 10.1109/lcn65610.2025.11146290 |
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