Service function chain mapping method based on delay guarantee
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| Publicado no: | Cluster Computing vol. 28, no. 5 (Aug 2025), p. 322 |
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| Autor principal: | |
| Outros Autores: | , , , , , , |
| Publicado em: |
Springer Nature B.V.
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| Assuntos: | |
| Acesso em linha: | Citation/Abstract |
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| 001 | 3242486585 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1386-7857 | ||
| 022 | |a 1573-7543 | ||
| 024 | 7 | |a 10.1007/s10586-024-04967-6 |2 doi | |
| 035 | |a 3242486585 | ||
| 045 | 2 | |b d20250801 |b d20250831 | |
| 100 | 1 | |a Zhuge, Bin |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 245 | 1 | |a Service function chain mapping method based on delay guarantee | |
| 260 | |b Springer Nature B.V. |c Aug 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Network function virtualization achieves the softwareization of network functions through virtualization technology, reducing operational costs but introducing challenges in network orchestration complexity. To deploy service function chains efficiently and cost-effectively in a network function virtualization environment, a latency-guaranteed, optimized mapping method is proposed. Firstly, a model that minimizes the total network deployment cost for service function chains is established, comprehensively considering user latency requirements and network resource constraints. Secondly, a service function chain mapping method based on an improved sparrow search algorithm is introduced. Finally, the simulation results show that the bandwidth resource utilization of the ISSA-SFCM algorithm is improved by 3.8% and 8.5%, respectively, compared to the control DP-COA algorithm and First-Fit algorithm, with a higher service function chain request acceptance rate and lower average network cost. | |
| 653 | |a Network function virtualization | ||
| 653 | |a Computer centers | ||
| 653 | |a Software | ||
| 653 | |a Control algorithms | ||
| 653 | |a Network topologies | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Optimization | ||
| 653 | |a Network latency | ||
| 653 | |a Mapping | ||
| 653 | |a Search algorithms | ||
| 653 | |a Linear programming | ||
| 653 | |a Operating costs | ||
| 653 | |a Resource utilization | ||
| 653 | |a Cloud computing | ||
| 653 | |a Heuristic | ||
| 700 | 1 | |a Cai, Xiaodan |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Zhang, Zitian |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Ren, Qianye |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Dong, Ligang |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Jiang, Xian |u Zhejiang Gongshang University, School of Information and Electronic Engineering (Sussex Artificial Intelligence Institute), Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Xu, Yueqian |u Zhejiang Gongshang University, Yingxian School of Philanthropy, Hangzhou, China (GRID:grid.413072.3) (ISNI:0000 0001 2229 7034) | |
| 700 | 1 | |a Lu, Lingrong |u UTStarcom Communications Ltd., Hangzhou, China (GRID:grid.413072.3) | |
| 773 | 0 | |t Cluster Computing |g vol. 28, no. 5 (Aug 2025), p. 322 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3242486585/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |