ABSTRACT

Modern telecommunication networks are comprised of a countless number of nodes exchanging data among them. In particular, multimedia traffic – composed of audio, video, and images – represents a challenging scenario requiring link optimisation techniques. The hub-and-spoke topology is frequently used to design more effective telecommunication networks. This work considers a hub-and-spoke network in which a large number of nodes are exchanging real-time multimedia data, and where the quantity of data sent from one node to another is a random variable. Given a fixed number of hubs, $p$, the goal is to select the best location for these $p$ hubs in order to minimise the total expected cost of transmission. This scenario is modelled as an uncapacitated single-allocation $p$-hub median problem under uncertainty conditions. Additionally, with the purpose of considering the effect of transmission delays on the video signal, service quality thresholds are assigned to every potential hub in the network. Since real-life networks tend to be large in size, we propose a simheuristic algorithm to cope with this stochastic and large-scale optimisation problem. A series of computational experiments illustrate these concepts and allow for testing the performance of our simheuristic approach. Finally, a statistical analysis of the obtained results is provided.

摘要

现代电信网络由无数个在它们之间交换数据的节点组成。特别是，由音频、视频和图像组成的多媒体流量代表了一个需要链路优化技术的具有挑战性的场景。中心辐射型拓扑经常用于设计更有效的电信网络。这项工作考虑了一个中心辐射型网络，其中大量节点正在交换实时多媒体数据，并且从一个节点发送到另一个节点的数据量是一个随机变量。给定固定数量的集线器，$p$，目标是为这些选择最佳位置$p$集线器，以最小化总的预期传输成本。该场景被建模为无容量的单一分配$p$- 不确定条件下的中值问题。此外，为了考虑传输延迟对视频信号的影响，服务质量阈值被分配给网络中的每个潜在集线器。由于现实生活中的网络往往规模较大，我们提出了一种模拟启发式算法来应对这种随机和大规模的优化问题。一系列计算实验说明了这些概念，并允许测试我们的模拟启发式方法的性能。最后，对所得结果进行统计分析。