The ability of TCP’s congestion control scheme to adapt the rate of traffic flows and fairly use all the available resources is one of the Internet’s pillars. So far, however, the elasticity of traffic has been disregarded in traffic engineering (TE) methodologies mainly because, only recently, the increase in access capacity has moved the bottlenecks from the access network to the operator network and hungry cloud-based applications have begun to use all the available bandwidth. We propose a new approach to TE with elastic demands which models the interaction between the network operator and the end-to-end congestion control scheme as a Stackelberg game . Given a set of elastic traffic demands only specified by their origin-destination pairs, the network operator chooses a set of routing paths (leader’s problem) which, when coupled with the fair bandwidth allocation that the congestion control scheme would determine for the chosen routing (follower’s problem), maximizes a network utility function. We present bilevel programming formulations for the above TE problem with two widely-adopted bandwidth allocation models, namely, max-min fairness and proportional fairness, and derive corresponding exact and approximate single-level mathematical programming reformulations. After discussing some key properties, we report on computational results obtained for different network topologies and instance sizes. Interestingly, even feasible solutions to our bilevel TE problems with large optimality gaps yield substantially higher network utility values than those obtained by solving a standard single-level TE problem and then fairly reallocating the bandwidth a posteriori .

中文翻译：

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弹性流量工程需要通过双层编程来公平分配带宽

TCP的拥塞控制方案适应流量速率并公平使用所有可用资源的能力是Internet的支柱之一。但是，到目前为止，流量的弹性在流量工程（TE）方法中一直被忽略，主要是因为直到最近，访问容量的增加才将瓶颈从访问网络转移到运营商网络，并且饥饿的基于云的应用程序已经开始使用所有可用带宽。我们提出了一种具有弹性需求的TE的新方法，该方法将网络运营商与端到端拥塞控制方案之间的交互建模为Stackelberg游戏 。给定一组仅由其源-目的地对指定的弹性流量需求，网络运营商选择一组路由路径（领导者问题），当与公平带宽分配结合时，拥塞控制方案将为所选路由确定路由路径（跟随者的问题），最大化网络实用程序功能。我们提出了针对上述TE问题的双层编程公式，其中采用了两种广泛采用的带宽分配模型，即最大-最小公平性和比例公平性，并推导了相应的精确和近似单层数学编程公式。在讨论了一些关键属性之后，我们报告了针对不同网络拓扑和实例大小获得的计算结果。有趣的是后验 。