Virtual Network Embedding for Evolving Networks

Cai, Zixing; Liu, Fang; Xiao, Nong; Chen, Honggang; Wang, Zhiying

doi:10.1109/glocom.2010.5683160

Cited by 75 publications

(44 citation statements)

References 9 publications

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“…[5], [6]). Studies involving this problem seek finding the optimal mapping of the virtual network demands over a shared physical substrate with scarce network resources.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of virtual optical networks for the future internet

Pages¹,

Perelló²,

Spadaro³

et al. 2012

2012 16th International Conference on Optical Network Design and Modelling (ONDM)

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Abstract-Optical network infrastructures can be partitioned into multiple parallel, dedicated virtual networks for a physical infrastructure sharing purpose. However, different transport technologies may impact in both the amount and the characteristics of the different virtual instances that can be built on top of a single physical infrastructure. To analyse the impact of the transport technology in this regard, we present exact Integer Linear Programming (ILP) formulations that address the off-line problem of optimally allocate a set of virtual networks in two kind of substrates: wavelength switching and spectrum switching. Both formulations serve the purpose to provide opaque transport services from the virtual network point of view, where electronic terminations are assumed in the virtual network nodes. We carry out a series of experiments to validate the presented formulations and determine which is the impact of both substrates in the number of virtual networks that can be optimally allocated in the transport network.

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“…[5], [6]). Studies involving this problem seek finding the optimal mapping of the virtual network demands over a shared physical substrate with scarce network resources.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of virtual optical networks for the future internet

Pages¹,

Perelló²,

Spadaro³

et al. 2012

2012 16th International Conference on Optical Network Design and Modelling (ONDM)

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“…Even if the mapping of all the virtual nodes is accomplished, the mapping of virtual links is still complicated. As a result, there are many VN mapping algorithms that can map as many VNs onto the physical network of edge-of-things computing as possible and minimize the VN mapping costs [26][27][28][29][30]. The VN mapping algorithm proposed in [26] maps the VNs under the guidance of minimizing mapping costs.…”

Section: Introductionmentioning

confidence: 99%

“…It shares the backup resource among different VNs without considering the backup resource sharing of a single VN during the mapping process. The author in [28] researched the redeployment and migration problem of the dynamic VN. The authors in [29,30] study the problem of VN mapping while considering the local failures of the physical network in edge-of-things computing.…”

Section: Introductionmentioning

confidence: 99%

Reliable design for virtual network requests with location constraints in edge-of-things computing

Zhang

Sangaiah

2018

J Wireless Com Network

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How to efficiently map virtual networks (VNs) onto a shared physical network is a challenging issue in the field of network virtualization in edge-of-things computing. Since an efficient VN mapping approach can reduce network resource consumption, lower latency, and enhance service reliability, it is important for both customers and network service providers. In this paper, we study the problem of mapping multiple VNs with geographic location constraints onto a physical network while considering the survivability and reliability requirements of each VN request in edge-ofthings based data centers. We present the model of this problem and propose a Geographic-Guided Survivable Multiple VN Mapping (GG-SMVNM) algorithm to efficiently solve this problem, which simultaneously considers resource sharing and mapping VN links and nodes in edge-of-things computing. Furthermore, we conduct a large amount of simulations to validate and evaluate our proposed approach. The simulation results show that the proposed method is superior to the existing solution.

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“…The authors in [9] and [10] study the VN embedding problem when the substrate network is dynamically changing. The approach in this paper differs from these works in that our consideration is on the changes in actual loading of the virtual networks, rather than on a 978-1-4799-0913-1/14/$31.00 c 2014 IEEE changing substrate network.…”

Section: Related Workmentioning

confidence: 99%

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Mijumbi

Gorricho

Serrat

et al. 2014

2014 IEEE Network Operations and Management Symposium (NOMS)

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Abstract-Network virtualisation is considerably gaining attention as a solution to ossification of the Internet. However, the success of network virtualisation will depend in part on how efficiently the virtual networks utilise substrate network resources. In this paper, we propose a machine learning-based approach to virtual network resource management. We propose to model the substrate network as a decentralised system and introduce a learning algorithm in each substrate node and substrate link, providing self-organization capabilities. We propose a multiagent learning algorithm that carries out the substrate network resource management in a coordinated and decentralised way. The task of these agents is to use evaluative feedback to learn an optimal policy so as to dynamically allocate network resources to virtual nodes and links. The agents ensure that while the virtual networks have the resources they need at any given time, only the required resources are reserved for this purpose. Simulations show that our dynamic approach significantly improves the virtual network acceptance ratio and the maximum number of accepted virtual network requests at any time while ensuring that virtual network quality of service requirements such as packet drop rate and virtual link delay are not affected.

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Virtual Network Embedding for Evolving Networks

Cited by 75 publications

References 9 publications

Optimal allocation of virtual optical networks for the future internet

Optimal allocation of virtual optical networks for the future internet

Reliable design for virtual network requests with location constraints in edge-of-things computing

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

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