基于多级流量预测的光互联网自适应虚拟拓扑重构策略

Lin Zhang, Kyunghee Lee, Chan-Hyun Youn, Hwan-geun Yeo
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引用次数: 15

摘要

本文研究了光互联网络虚拟拓扑重构阶段出现的问题。这种重新配置过程意味着更改虚拟拓扑以响应更高层中不断变化的流量模式。我们将最优重构策略表述为一个多阶段决策问题,以在无限视界上最大化期望回报和成本函数。为了解决启发式方法带来的连续逼近问题,我们考虑了交通预测。为了实现最优的重构策略,提出了一种新的启发式重构算法——基于预测的多阶段重构方法。仿真结果表明,在物理资源有限的情况下,我们的重构策略明显优于传统的重构策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive virtual topology reconfiguration policy employing multi-stage traffic prediction in optical Internet
This paper studies the issues arising in the virtual topology reconfiguration phase of optical Internet networks. This reconfiguration process means to change the virtual topology in response to the changing traffic patterns in the higher layer. We formulate the optimal reconfiguration policy as a multi-stage decision-making problem to maximize the expected reward and cost function over an infinite horizon. To counter the continual approximation problem brought by heuristic approach, we take the traffic prediction into consideration. We propose a new heuristic reconfiguration algorithm called prediction based multi-stage reconfiguration approach to realize the optimal reconfiguration policy. Simulation results show that our reconfiguration policy significantly outperforms the conventional one, while the required physical resources are limited.
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