弹性光网络流量预测辅助路由算法

A. Valkanis, Georgios I. Papadimitriou, Petros Nicopolitidis, G. Beletsioti, Emmanouel Varvarigos
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引用次数: 8

摘要

弹性光网络(eon)预计将满足未来几年应用的发展以及5G和物联网技术的实施所带来的巨大带宽需求。利用永续网络在资源管理方面提供的灵活性,为研究界提出了挑战,即如何建立将永续网络效率最大化的机制。该方向的主要研究方向之一是对骨干网的流量进行预测并利用这些信息进行有效的资源管理。在这项工作中,我们提出了一种流量预测辅助路由算法,以提高弹性光网络的整体性能。详细的仿真场景验证了所提出的路由算法的有效性,与文献中的相关算法相比,该算法提高了网络阻塞概率。
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A Traffic Prediction assisted Routing Algorithm for Elastic Optical Networks
Elastic optical networks (EONs) are expected to cover the huge bandwidth demands, which will arise in the coming years from both the applications’ evolution and the implementation of 5G and Internet of Things technologies. Harvesting the flexibility offered by EONs in the management of resources, poses challenges for the research community in terms of creating mechanisms that will maximize their efficiency. One of the main research fields in this direction is the prediction of the traffic in the backbone networks and the utilization of this information for efficient resource management. In this work, we present a traffic prediction assisted routing algorithm for elastic optical networks, which improves their overall performance. Detailed simulation scenarios confirm the effectiveness of the proposed routing algorithm, which improves the network blocking probability in comparison to related algorithms from the literature.
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