基于混合生物启发的鲁棒网络切片设计问题

T. Bauschert, Varun S. Reddy
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引用次数: 0

摘要

我们考虑在给定的物理基板网络基础设施上提供通用网络切片请求的任务-这是下一代网络环境中出现的问题-在流量不确定的情况下,以最小化为适应网络切片而产生的资本和运营支出为目标。由于所得到的公式即使对于中等大小的问题实例也难以使用商业MIP求解器来解决,因此我们设计了一种混合偏随机密钥遗传算法来解决鲁棒网络切片设计问题。最后,我们使用来自SNDlib[1]的实际数据集对所提出的解决方案方法进行了性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Bio-Inspired Heuristics for the Robust Network Slice Design Problem
We consider the task of provisioning a generic network slice request on a given physical substrate network infrastructure-a problem that arises in the context of next generation networks-under traffic uncertainty, with the objective of minimising the capital and operational expenditures incurred to accommodate the network slice. As the resulting formulation can be hard to tackle using commercial MIP solvers even for problem instances of moderate size, we devise a hybrid biased-random key genetic algorithm to solve the robust network slice design problem. Finally, we present a performance evaluation of the proposed solution methodologies using realistic datasets from SNDlib [1].
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