Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement
Virtual network function (VNF) can provide various network services and is widely deployed in inter-data centers elastic optical networks (Inter-DC EONs). Routing and VNF deployment for VNF service chain (VNF-SC) in Inter-DC EONs is a very important and well-known NP-hard problem. For this problem,...
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IEEE
2019-01-01
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Online Access: | https://ieeexplore.ieee.org/document/8935202/ |
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author | Hejun Xuan Shiwei Wei Yan Feng Daohua Liu Yanling Li |
author_facet | Hejun Xuan Shiwei Wei Yan Feng Daohua Liu Yanling Li |
author_sort | Hejun Xuan |
collection | DOAJ |
description | Virtual network function (VNF) can provide various network services and is widely deployed in inter-data centers elastic optical networks (Inter-DC EONs). Routing and VNF deployment for VNF service chain (VNF-SC) in Inter-DC EONs is a very important and well-known NP-hard problem. For this problem, if determining the number and locations of data centers is additionally considered, it will be more complicated. In this paper, we investigate a network planning problem in Inter-DC EONs by determining all these factors, i.e, by determining not only the optimal routing and the optimal VNF deployment for VNF-SCs, but also the optimal number and locations of data centers. To achieve this purpose, we first establish a bi-level programming model in which the leader's objective is to minimize the number of data centers and find the best locations of data centers so that we can get a balanced VNF deployment on data centers. To determine the optimal routing and VNF deployment for VNF-SCs, the follower's objective is to minimize the maximum index of used frequency slots and the number of used frequency slots. Then, to solve the proposed model effectively, tailor-made crossover, mutation and local search operators are designed, and based on these operators, an efficient bi-level hybrid memetic algorithm (BiHMA) is proposed. Finally, to test the effectiveness of the proposed model and the efficiency of the proposed algorithm, the simulation experiments are conducted on two widely used networks, and experimental results indicate that the proposed algorithm has a higher efficiency than compared algorithms. |
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format | Article |
id | doaj.art-055f5cab94e44ab09c9ddf2394ee3aae |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-14T10:49:19Z |
publishDate | 2019-01-01 |
publisher | IEEE |
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spelling | doaj.art-055f5cab94e44ab09c9ddf2394ee3aae2022-12-21T23:05:18ZengIEEEIEEE Access2169-35362019-01-01718576018577210.1109/ACCESS.2019.29603958935202Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers PlacementHejun Xuan0https://orcid.org/0000-0002-3062-1591Shiwei Wei1https://orcid.org/0000-0002-2324-4791Yan Feng2https://orcid.org/0000-0003-0054-2435Daohua Liu3https://orcid.org/0000-0002-6656-359XYanling Li4https://orcid.org/0000-0002-5766-898XSchool of Computer and Information Technology, Xinyang Normal University, Xinyang, ChinaSchool of Computer and Technology, Guilin University of Aerospace Technology, Guilin, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang, ChinaVirtual network function (VNF) can provide various network services and is widely deployed in inter-data centers elastic optical networks (Inter-DC EONs). Routing and VNF deployment for VNF service chain (VNF-SC) in Inter-DC EONs is a very important and well-known NP-hard problem. For this problem, if determining the number and locations of data centers is additionally considered, it will be more complicated. In this paper, we investigate a network planning problem in Inter-DC EONs by determining all these factors, i.e, by determining not only the optimal routing and the optimal VNF deployment for VNF-SCs, but also the optimal number and locations of data centers. To achieve this purpose, we first establish a bi-level programming model in which the leader's objective is to minimize the number of data centers and find the best locations of data centers so that we can get a balanced VNF deployment on data centers. To determine the optimal routing and VNF deployment for VNF-SCs, the follower's objective is to minimize the maximum index of used frequency slots and the number of used frequency slots. Then, to solve the proposed model effectively, tailor-made crossover, mutation and local search operators are designed, and based on these operators, an efficient bi-level hybrid memetic algorithm (BiHMA) is proposed. Finally, to test the effectiveness of the proposed model and the efficiency of the proposed algorithm, the simulation experiments are conducted on two widely used networks, and experimental results indicate that the proposed algorithm has a higher efficiency than compared algorithms.https://ieeexplore.ieee.org/document/8935202/EONsdata centers placementbi-level optimizationMemetic algorithm |
spellingShingle | Hejun Xuan Shiwei Wei Yan Feng Daohua Liu Yanling Li Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement IEEE Access EONs data centers placement bi-level optimization Memetic algorithm |
title | Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement |
title_full | Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement |
title_fullStr | Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement |
title_full_unstemmed | Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement |
title_short | Bi-Level Programming Model and Algorithm for VNF Deployment With Data Centers Placement |
title_sort | bi level programming model and algorithm for vnf deployment with data centers placement |
topic | EONs data centers placement bi-level optimization Memetic algorithm |
url | https://ieeexplore.ieee.org/document/8935202/ |
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