Routing-Led Evolutionary Algorithm for Large-Scale Multi-Objective VNF Placement Problems
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915681785610240 |
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| author | Mao, Peili Billingsley, Joseph Miao, Wang Mi, Geyong Li, Ke |
| author_facet | Mao, Peili Billingsley, Joseph Miao, Wang Mi, Geyong Li, Ke |
| contents | Modern data centers contain thousands of servers making them major consumers of electricity. To minimize their environmental impact, it is critical that we use their resources efficiently. In this paper we study how to discover the optimal placement of virtual network functions in large scale data centers. We propose a novel parallel metaheuristic, fast heuristic objective functions of the QoS and new memory efficient data structures for large networks. We further identify a simple, fast heuristic that can produce competitive solutions to very large problem instances. Using these new concepts, we are able to find high quality solutions for data centres with up to 64,000 servers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_15339 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Routing-Led Evolutionary Algorithm for Large-Scale Multi-Objective VNF Placement Problems Mao, Peili Billingsley, Joseph Miao, Wang Mi, Geyong Li, Ke Neural and Evolutionary Computing Modern data centers contain thousands of servers making them major consumers of electricity. To minimize their environmental impact, it is critical that we use their resources efficiently. In this paper we study how to discover the optimal placement of virtual network functions in large scale data centers. We propose a novel parallel metaheuristic, fast heuristic objective functions of the QoS and new memory efficient data structures for large networks. We further identify a simple, fast heuristic that can produce competitive solutions to very large problem instances. Using these new concepts, we are able to find high quality solutions for data centres with up to 64,000 servers. |
| title | Routing-Led Evolutionary Algorithm for Large-Scale Multi-Objective VNF Placement Problems |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2512.15339 |