Abstract

Abstract

Traditional traffic measurements meter throughput on time scales in the order of 5 minutes, e.g., using the Multi Router Traffic Grapher (MRTG) tool. The time scale on which users and machines perceive Quality of Service (QoS) is, obviously, orders of magnitudes smaller. One of many possible reasons for degradation of the perceived quality, is congestion on links along the path network packets traverse. In order to prevent quality degradation due to congestion, network links have to be dimensioned in such a way that they appropriately cater for traffic bursts on time scales similarly small to the time scale that determines perceived QoS. It is well-known that variability of link load on small time scales (e.g., 10 milliseconds) is larger than on large time scales (e.g., 5 minutes). Few quantitative figures are known, however, about the magnitude of the differences between fine and coarse-grained measurements. The novel aspect of this paper is that it quantifies the differences in measured link load on small and large time scales. The paper describes two case studies. One of the surprising results is that, even for a network with 2000 users, the difference between short-term and long-term average load can be more than 100%. This leads to the conclusion that, in order to prevent congestion, it may not be sufficient to use the 5 minute MRTG maximum and add a small safety margin. Document type: Part of book or chapter of book

Abstract

The Spanish machinery-building sector is highly fragmented and focused on prototyping. Small and medium-sized enterprises (SMEs) cannot afford to test prototypes or to use advanced computer-aided tools. They do not share a formal knowledge base, but they unofficially copy the applied solutions in each other’s products. This conservative approach leads to the overdimensioning of components, and the lack of technical knowledge can lead to the underdimensioning of components for a new design. To bridge this gap, the present work describes the use of a low-priced simulation software to optimize the thickness of an autoclave vessel for the canning industry. The information that was provided by the simulations, which was similar to that obtained by Ansys, allowed the manufacturer to select the optimal thickness of the vessel. This demonstrates that day-to-day design and further innovation can be supported by high-end expensive tools and by affordable tools.

Abstract