Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shuai; Wang, Xiaoli

doi:10.1016/j.optcom.2017.05.065

Cited by 19 publications

(10 citation statements)

References 27 publications

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“…In [11,14,45], the authors have proposed efficient approaches to solve VNE in EON for network slicing to guarantee the service requirements. Spatial resources of optical network are also considered in some works [47][48][49], which refer to fiber cores or modes in multi-core fibers or multi-mode fibers, or even single-mode fiber bundles. The proposed genetic algorithm in [48] has obtained the optimal VNE schemes with core allocation to efficiently by designing tailor-made encoding scheme, crossover, and mutation operators.…”

Section: Optical Networkmentioning

confidence: 99%

“…Spatial resources of optical network are also considered in some works [47][48][49], which refer to fiber cores or modes in multi-core fibers or multi-mode fibers, or even single-mode fiber bundles. The proposed genetic algorithm in [48] has obtained the optimal VNE schemes with core allocation to efficiently by designing tailor-made encoding scheme, crossover, and mutation operators. Some additional constraints for VNE should be considered for optical network domain such as spectrum continuity, spectrum contiguity, and physical layer impairments [50][51][52].…”

Section: Optical Networkmentioning

confidence: 99%

“…In order to further improve the performance, metaheuristic-based coordinated VNE algorithms are proposed. The authors of [48] propose an effective genetic algorithm for virtual optical network mapping, core allocation, and spectrum assignment in EONs using multi-core fibers. The objective is minimizing the maximum index of used frequency slots, which is regard as spectrum usage in this section.…”

Section: Coordinated Vne Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges

Zong

Feng

Guan

et al. 2020

Sensors

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The emerging 5G applications and the connectivity of billions of devices have driven the investigation of multi-domain heterogeneous converged optical networks. To support emerging applications with their diverse quality of service requirements, network slicing has been proposed as a promising technology. Network virtualization is an enabler for network slicing, where the physical network can be partitioned into different configurable slices in the multi-domain heterogeneous converged optical networks. An efficient resource allocation mechanism for multiple virtual networks in network virtualization is one of the main challenges referred as virtual network embedding (VNE). This paper is a survey on the state-of-the-art works for the VNE problem towards multi-domain heterogeneous converged optical networks, providing the discussion on future research issues and challenges. In this paper, we describe VNE in multi-domain heterogeneous converged optical networks with enabling network orchestration technologies and analyze the literature about VNE algorithms with various network considerations for each network domain. The basic VNE problem with various motivations and performance metrics for general scenarios is discussed. A VNE algorithm taxonomy is presented and discussed by classifying the major VNE algorithms into three categories according to existing literature. We analyze and compare the attributes of algorithms such as node and link embedding methods, objectives, and network architecture, which can give a selection or baseline for future work of VNE. Finally, we explore some broader perspectives in future research issues and challenges on 5G scenario, field trail deployment, and machine learning-based algorithms.

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Section: Optical Networkmentioning

confidence: 99%

Section: Optical Networkmentioning

confidence: 99%

Section: Coordinated Vne Algorithmsmentioning

confidence: 99%

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Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges

Zong

Feng

Guan

et al. 2020

Sensors

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“…However, a challenge is how to map a large number of VONs with different topologies to the physical network while reaching some purpose, such as energy consumption, ratio of blocking, performance of the network [30]. In recent years, there are large number of researches focusing their research on the VONs mapping problem and some related problems [23], [42].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

Self Cite

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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.

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“…To tackle this issue, elastic optical networks (EONs) [3] are proposed to realize flexible and efficient spectrum allocation with much finer spectrum granularity. In particular, EONs provide just-right bandwidth for the arriving request connection dynamically, which brings better spectrum assignment flexibility [4,5]. Orthogonal frequency division multiplexing is a multi-carrier modulation technology.…”

Section: Introductionmentioning

confidence: 99%

Grey Wolf Algorithm and Multi-Objective Model for the Manycast RSA Problem in EONs

et al. 2019

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Manycast routing and spectrum assignment (RSA) in elastic optical networks (EONs) has become a hot research field. In this paper, the mathematical model and high efficient algorithm to solve this challenging problem in EONs is investigated. First, a multi-objective optimization model, which minimizes network power consumption, the total occupied spectrum, and the maximum index of used frequency spectrum, is established. To handle this multi-objective optimization model, we integrate these three objectives into one by using a weighted sum strategy. To make the population distributed on the search domain uniformly, a uniform design method was developed. Based on this, an improved grey wolf optimization method (IGWO), which was inspired by PSO (Particle Swarm Optimization, PSO) and DE (Differential Evolution, DE), is proposed to solve the maximum model efficiently. To demonstrate high performance of the designed algorithm, a series of experiments are conducted using several different experimental scenes. Experimental results indicate that the proposed algorithm can obtain better results than the compared algorithm.

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Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

Cited by 19 publications

References 27 publications

Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges

Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges

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

Grey Wolf Algorithm and Multi-Objective Model for the Manycast RSA Problem in EONs

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