Spectrum trading between virtual optical networks with time-varying traffic in an elastic optical network

Spectrum trading between virtual optical networks with time-varying traffic in an elastic optical network
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弹性光网络中具有时变流量的虚拟光网络之间的频谱交易

DOI:
10.1364/jocn.377462
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发表时间:
2020-01
期刊:
IEEE/OSA Journal of Optical Communications and Networking
影响因子:
--
通讯作者:
Gangxiang Shen
Gangxiang Shen
中科院分区:
其他
文献类型:
--
作者:
Shifeng Ding;Sanjay K. Bose;Gangxiang Shen

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网络虚拟化可以通过使支持不同服务的多个虚拟网络共存来提高物理网络的利用率。对于弹性光网络,网络虚拟化将创建嵌入在同一物理光网络中的多个虚拟光网络(VON)。传统上,这些VON中的每一个被分配有固定量的网络资源。然而,VON上的业务需求通常是动态的,随时间变化。这导致分配的固定资源与用户实际需要的资源不匹配。因此,一些用户服务可能被阻塞,并且由每个VON提供的服务质量可能被降级。为了克服这种不匹配所造成的缺点,我们提出了一种网络资源共享方案,称为频谱交易(ST),根据其实际容量的要求,不同的虚拟网络之间的交易频谱资源,以更好的整体频谱利用率。线性规划(ILP)模型的开发,以模拟不同的ST的情况下,和启发式算法的开发,以解决在大型网络中的ST。仿真研究表明,所提出的ST计划是有效的,在显着提高总流量需求的VON进行高达20%的测试网络中考虑,而不会带来任何额外的硬件成本。
Network virtualization can improve the utilization of a physical network by enabling the coexistence of multiple virtual networks supporting different services. For an elastic optical network, network virtualization would create a number of virtual optical networks (VONs) embedded in the same physical optical network. Conventionally, each of these VONs is allocated with a fixed amount of network resources. However, the traffic demand on a VON is usually dynamic, varying over time. This leads to a mismatch between the fixed resource assigned and the actual resource required by users. Therefore, some user services may be blocked and the quality of service provided by each VON may be degraded. To overcome the disadvantage caused by this mismatch, we propose a network resource-sharing scheme, called spectrum trading (ST), which trades spectrum resources between different VONs based on their actual capacity requirements, for better overall spectrum utilization. Integer linear programming (ILP) models are developed to model the different ST scenarios, and heuristic algorithms are developed to tackle ST in large networks. Simulation studies show that the proposed ST scheme is effective in significantly improving the total traffic demand carried by VONs by up to 20% in the test networks considered, while not bringing in any additional hardware cost.
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