需求不确定网络中最短路径与多枢纽路由的比较
Shortest Path versus Multi-Hub Routing in Networks with Uncertain Demand
摘要：
我们研究一类强大的网络设计问题的动机需要扩展核心网络，以满足日益动态的容量需求。过去的工作集中在设计网络，以支持所有软管矩阵（所有矩阵不超过边际界限的节点）。如果有关于交通模式的额外信息，这种模型可能过于保守。另一个极端是固定需求模型，在该模型中，网络设计为支持峰值点对点需求。我们引入了一个加盖软管模型，以探索更广泛的流量矩阵，其中包括上述两个特殊情况。众所周知，软管模型的最优设计总是由单枢纽布线确定，而固定需求模型的最优设计是基于最短路径布线。我们揭示了更广泛的空间的上限软管矩阵，以了解哪些交通模型是更短的路径，而不是集线器一样。为了解决中间的空间，我们使用分层多集线器路由模板，集线器和树路由的泛化。特别是，我们表明，通过将峰值容量添加到软管模型中，单集线器树路由模板不再具有成本效益。这引发了一类鲁棒网络设计（RND）问题的研究，仅限于这些模板。我们的实证分析是基于这个新的层次RND问题的启发式。我们还建议，它是可以定义一个路由指标，占优势的边际和峰值需求，并使用此信息来选择适当的路由模板。我们基准我们的方法对其他知名的路由模板，使用代表性的运营商网络和各种不同的上限软管流量的需求，参数化的相对重要性，他们的边缘，而不是他们的点对点的峰值需求。
英文摘要：
We study a class of robust network design problems motivated by the need to scale core networks to meet increasingly dynamic capacity demands. Past work has focused on designing the network to support all hose matrices (all matrices not exceeding marginal bounds at the nodes). This model may be too conservative if additional information on traffic patterns is available. Another extreme is the fixed demand model, where one designs the network to support peak point-to-point demands. We introduce a capped hose model to explore a broader range of traffic matrices which includes the above two as special cases. It is known that optimal designs for the hose model are always determined by single-hub routing, and for the fixed- demand model are based on shortest-path routing. We shed light on the wider space of capped hose matrices in order to see which traffic models are more shortest path-like as opposed to hub-like. To address the space in between, we use hierarchical multi-hub routing templates, a generalization of hub and tree routing. In particular, we show that by adding peak capacities into the hose model, the single-hub tree-routing template is no longer cost-effective. This initiates the study of a class of robust network design (RND) problems restricted to these templates. Our empirical analysis is based on a heuristic for this new hierarchical RND problem. We also propose that it is possible to define a routing indicator that accounts for the strengths of the marginals and peak demands and use this information to choose the appropriate routing template. We benchmark our approach against other well-known routing templates, using representative carrier networks and a variety of different capped hose traffic demands, parameterized by the relative importance of their marginals as opposed to their point-to-point peak demands.
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