A Novel Optimal Mapping Algorithm With Less Computational Complexity for Virtual Network Embedding

Cao, Haotong; Zhu, Yongxu; Zheng, Gan; Yang, Longxiang

doi:10.1109/tnsm.2017.2778106

Cited by 78 publications

(46 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We compare the proposed algorithm GAL with three best performance algorithms, which solve the VONs mapping problem, denoted by CAN-A, LCSD and GRC-SVNE, respectively. CAN-A, LCSD and GRC-SVNE denote the algorithms of proposed in literature [4], literature [6] and literature [50], respectively. CAN-A algorithm lies in constructing the candidate substrate node subset and the candidate substrate path subset before embedding.…”

Section: A Parameters Settingmentioning

confidence: 99%

A New Bi-Level Mathematical Model and Algorithm for VONs Mapping Problem

et al. 2020

View full text Add to dashboard Cite

Elastic optical networks (EONs) virtualization can allow the virtual optical networks (VONs) to utilize all the physical resources of EONs, and can attain a high performance of the networks. However, the optimal scheme for VONs mapping should be determined. To tackle these challenges, a bi-level mathematical model is established. leader's and follower's objectives are to minimize energy consumption and the maximum index of used frequency slots, respectively. The bi-level mathematical model can determine the optimal schemes of VONs mapping. To solve the mathematical model effectively, a uniform design method is applied to generate initial population for the lower level problem. In addition, To solve the whole model effectively, a tailor-made encoding, population initialization, genetic operators and local search operator are designed. An efficient genetic algorithm with local search operator is proposed for the bilevel mathematical model. To evaluate the mathematical model and the designed algorithm, a large number of experiments are performed on three kinds of the widely used networks, and the experimental results indicate that the effectiveness of the proposed bi-level mathematical model and designed algorithms.

show abstract

Section: A Parameters Settingmentioning

confidence: 99%

A New Bi-Level Mathematical Model and Algorithm for VONs Mapping Problem

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In fact, the Z ratio represents the average number of additional links or number of slave nodes per virtual network. e curves of ProactiveP If |Neigh| �� speedup do (6) Remove the node with the lowest CPU value from Neigh (7) Sum � Sum-CPU (the node with the lowest CPU value) (8) End if (9) add P[j] to Neigh in Figures 3 and 4 are smoother and higher than the other two because the algorithm maps each virtual node to multiple substrate nodes regardless of the actual situation of network resources. e reason why the two curves of EPVNE in Figures 3 and 4 are higher than that of LazyP is that the acceptance rate of EPVNE is high.…”

Section: Performance Analysismentioning

confidence: 99%

“…Network virtualization technology allows multiple virtual heterogeneous networks to coexist on top of a shared underlying physical network infrastructure. Each virtual network is a piece of resources of the underlying physical network, which consists of virtual nodes (for example, virtual routers and cloud computing center) and virtual links provider (ISP) into two separate entities: infrastructure provider (InP) and service provider (SP) [8,9]. In such a network environment, an infrastructure provider manages a substrate network (SN), which is composed of substrate nodes and physical communication links.…”

Section: Introductionmentioning

confidence: 99%

EPVNE: An Efficient Parallelizable Virtual Network Embedding Algorithm

Zhang

2019

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Virtual network embedding (VNE) problem is a key issue in network virtualization technology, and much attention has been paid to the virtual network embedding. However, very little research work focuses on parallelized virtual network embedding problems which assumes that the substrate infrastructure supports parallel computing and allows one virtual node to be mapped to multiple substrate nodes. Based on the work of Liang and Zhang, we extend the well-known VNE to parallelizable virtual network embedding (PVNE) in this paper. Furthermore, to the best of our knowledge, we give the first formulation of the PVNE problem. A new heuristic algorithm named efficient parallelizable virtual network embedding (EPVNE) is proposed to reduce the cost of embedding the VN request and increase the VN request acceptance ratio. EPVNE is a two-stage mapping algorithm, which first performs node mapping and then performs link mapping. In the node mapping phase, we present a simple and efficient virtual node and physical node sorting formula and perform the virtual node mapping in order. When mapping virtual nodes, we map virtual nodes to physical nodes that just meet the CPU requirements. Substrate nodes with more CPU resources will be retained for subsequent virtual network mapping requests. In the link mapping phase, Dijkstra’s algorithm is used to find a substrate path for each virtual link. Finally, simulations are carried out and simulation results show that our algorithm performs better than the existing heuristic algorithms.

show abstract

“…In order to accelerate the convergence speed and avoid sucking in local optimal solution [25], we must consider not only the embedding sequence of virtual nodes but also the selection of substrate nodes to be embedded. Therefore, before our embedding process, virtual nodes are first ranked in an appropriate mapping sequence.…”

Section: Topology-oriented Vne Algorithmmentioning

confidence: 99%

Topology-Oriented Virtual Network Embedding Approach for Data Centers

2019

View full text Add to dashboard Cite

Currently, data centers have become an attractive candidate for users that require IT resources in the form of virtual networks to run their applications. Optimal mapping of the virtual network on the top of the substrate network with resource constraint is called virtual network embedding (VNE) problem. Most of the VNE algorithms are general algorithms for random topology and not suitable for data centers due to particular topological characteristics. To solve the VNE problem in data centers, this paper develops a topology-oriented algorithm based on the Discrete Particle Swarm Optimization (DPSO). We first develop a maximum spanning algorithm to compute the ranking of virtual nodes based on, not only its bandwidth and degree, but also its connectivity in the entire virtual network. Then, the virtual networks are embedded onto the substrate network according to the connectivity ranking result by a DPSO-based algorithm, in which we also propose a topological heuristic information of substrate network and combine it into the particle search process for boosting convergence speed and revenue/cost ratio of substrate network. The evaluation results show that the proposed algorithm can improve the optimization performance of VNE by comparing with a few existing algorithms. INDEX TERMS Data center, virtual resource allocation, virtual network embedding, discrete particle swarm optimization.

show abstract

A Novel Optimal Mapping Algorithm With Less Computational Complexity for Virtual Network Embedding

Cited by 78 publications

References 46 publications

A New Bi-Level Mathematical Model and Algorithm for VONs Mapping Problem

A New Bi-Level Mathematical Model and Algorithm for VONs Mapping Problem

EPVNE: An Efficient Parallelizable Virtual Network Embedding Algorithm

Topology-Oriented Virtual Network Embedding Approach for Data Centers

Contact Info

Product

Resources

About