Statistische Leistungsschranken für Computernetzwerke und Kommunikationssysteme

实现具有高度可扩展性的概念对互联网的成功至关重要。因此，骨干路由器转发聚合流量，避免任何按流处理。流之间的公平性通过端到端拥塞控制来实现，然而，端到端拥塞控制并不普遍适用。因此，今天的互联网只实现了一种基本服务，称为Best-Effort，它不提供任何类型的性能保证。最近的区分服务体系结构通过添加一些额外的服务类来扩展单服务互联网，理想情况下具有定义的服务保证，同时保持流量聚合的概念。然而，在聚合调度网络的性能保证的推导是复杂的，仍然受到研究。这个问题是由难以量化的流量聚合和复用效应引起的。该项目的目的是发展一个框架的聚合调度网络的性能评估。应用领域是多方面的，范围从尺寸到入场控制。预期工作的一个重要部分是开发一个简洁的概率网络演算应用概念的理论有效带宽。我们的目标是通过允许某些违规概率来扩展今天的最坏情况分析。

The realization of concepts with high scalability has been crucial to the success of the Internet. Consequently, backbone routers forward aggregated traffic, avoiding any per-flow treatment. Fairness among flows is approached by end-to-end congestion control, which, however, is not generally applicable. Hence, today's Internet implements only one basic service, called Best-Effort, that does not provide performance guarantees of any kind. The recent Differentiated Services architecture extends the single service Internet by adding few additional service classes, ideally with defined service guarantees, while maintaining the concept of traffic aggregation. However, in Aggregate scheduling networks the derivation of performance guarantees is complicated and still subject to research. The problem is caused by traffic aggregation and multiplexing effects that are hard to quantify. This project aims at evolving a framework for performance evaluation of Aggregate scheduling networks. The areas of application are manifold and range from dimensioning to admission control. A significant part of the intended work is the development of a concise probabilistic Network Calculus applying concepts from the theory of effective bandwidths. The goal is to extend today's worst-case analysis by allowing for certain violation probabilities.