Research on Optimized Deployment of Virtual Network Functions in Network Function Virtualization Environment
Guardat en:
| Publicat a: | Journal of Physics: Conference Series vol. 1748, no. 3 (Jan 2021) |
|---|---|
| Autor principal: | |
| Altres autors: | |
| Publicat: |
IOP Publishing
|
| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text - PDF |
| Etiquetes: |
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 2513107371 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1742-6588 | ||
| 022 | |a 1742-6596 | ||
| 024 | 7 | |a 10.1088/1742-6596/1748/3/032020 |2 doi | |
| 035 | |a 2513107371 | ||
| 045 | 2 | |b d20210101 |b d20210131 | |
| 100 | 1 | |a Liu, Mingyue |u Electronics and Communication Engineering, Beijing University of Aeronautics and Astronautics, Beijing, Beijing, 100191, China | |
| 245 | 1 | |a Research on Optimized Deployment of Virtual Network Functions in Network Function Virtualization Environment | |
| 260 | |b IOP Publishing |c Jan 2021 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a This paper mainly studies the optimization of dynamically arrived SFCs deployment in the SDN scenarios, and optimizes the end-to-end delay and bandwidth consumption during the deployment. First we build the model of the optimization problem, it is expressed as a 0-1 planning problem. We use ILP to get the optimal solution, cause the problem is NP hard, its runtime increases as network scales increases, so we choose the heuristic algorithm instead to reduce algorithm runtime. During our heuristic algorithm, we design a new method to sort VNFs and network nodes, then use the greedy algorithm to select nodes literately to place VNFs, in order to avoid local optimality, further use the simulated annealing algorithm with the results of the greedy algorithm as its initial solution, and design two methods to generate new deployments, and still repeat iterating to find a better deployment until reaching iteration limits. This paper also considers the SFCs’ lifecycle and trade-off between the two parameters. The simulation proves that the algorithm proposed in this paper can significantly reduce the end-to-end delay and bandwidth consumption than the traditional method, and 80% of its results are very close to the optimal solution with less than 5% error, and the ratio of its runtime and optimal solution’s is at most 0.003, the algorithm also has certain applicability and can be used in other scenarios. | |
| 653 | |a Algorithms | ||
| 653 | |a Virtual networks | ||
| 653 | |a Consumption | ||
| 653 | |a Simulated annealing | ||
| 653 | |a Iterative methods | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Optimization | ||
| 653 | |a Nodes | ||
| 653 | |a Greedy algorithms | ||
| 653 | |a Physics | ||
| 700 | 1 | |a Liu, Feng |u Electronics and Communication Engineering, Beijing University of Aeronautics and Astronautics, Beijing, Beijing, 100191, China | |
| 773 | 0 | |t Journal of Physics: Conference Series |g vol. 1748, no. 3 (Jan 2021) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2513107371/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2513107371/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |