Model-Based Monitoring in Large-Scale Distributed Systems

Monitoring remains an important problem in computer science. This thesis describes which monitor information is needed to analyze distributed service environments. This thesis also describes how to get these information and how to store them in a monitoring database. The resulting model is used to describe a distributed media content environment and a simulation system that runs on the CLIC helps to generate measurements as in real systems.Monitoring ist ein wichtiges Problem in der Informatik. In dieser Arbeit werden die benoetigten Daten beschrieben, welche zur Analyse von verteilten Dienstumgebungen dienen. Weiterhin wird beschrieben, wie man diese Daten messen und in einer geeigneten Datenbank speichern kann. Das daraus entstehende Modell wird verwendet um eine verteilte Medien-Daten-Umgebung zu beschreiben und eine Simulation auf dem CLIC erzeugt Messdaten wie sie in realen Systemen vorkommen

Un Confronto tra Tecniche MPEG-DASH e SVC

Il concetto base di questa proposta risulta essere lo streaming dei media e di preciso quello dinamico. Veranno presentate varie proposte che hanno cercato di affrontare questo grande problema. Nel dettaglio, sono presentate due tecnologie [SVC, MPEGDASH] usate per lo streaming adattivo, le loro architetture, come raggiungono lo stesso risultato prendendo strade diverse e dove devono essere applicate rispettivamente. Inoltre, si discute per capire le loro funzionalita' in termini di compressione di flussi multimediali, decodifica e flessibilita' prendendo in considerazione vari test effettuati da terze parti

Techniques for improving the capacity of video-on-demand systems

In this paper we present two techniques to improve the capacity of video on demand sysrems. Video on demand is an elecrronic video rental system in which clients requesr and play videos on-demand. Video on demand system can be implemented over an existing cable TV network or an upgraded ADSL network. The two techniques used to improve rhe capacity of video on-demand systems are segmentation and multicasring. Segmentation consists of dividing the video into several fired length segments. and then transmitting rhe segments at regular intervals instead of transmitting the entire video continuously. Mulricasring assumes that each subscriber has a limited storage space, so same video segments can be multicast fo subscribers simultaneously. Results of a comprehensive simulation srudy presented in the paper show a significant improvement in the capacity of rhe system when these two techniques are applied. In evaluating video on-demand systems we considered the following parameters: rhe number of users supported, the number of videos played per day, and the number of requests rejected per day. 1