Speaker: Professor Krzysztof Pawlikowski, University of Canterbury, Christchurch, New Zealand
Abstract: Advances of computer technology initiated in the twentieth century have resulted in adoption of computer simulation as the most popular tool of performance evaluation studies of such complex stochastic dynamic systems as e.g. modern multimedia telecommunication networks. Such wide-spread reliance on simulation studies raises the question of credibility of results from such studies. This question needs to be answered before computer simulation can be objectively accepted as an independent, self-sufficient paradigm of scientific investigations. In this talk, having briefly overviewed the main necessary conditions of any trustworthy simulation study conducted for performance evaluation of stochastic dynamic systems, we will focus on simulation studies with on-line output data analysis. The perils and pitfalls of quantitative discrete-event computer simulation will be considered, together with its fast distributed version, known as Multiple Replications in Parallel, implemented in Akaroa2, a unique controller of quantitative stochastic simulation.
Speaker Biography: Krzysztof Pawlikowski is a Professor in Computer Science & Software Engineering at the University of Canterbury, in Christchurch, New Zealand. He received a Ph.D. degree in Computer Engineering from Gdansk University of Technology, Poland, and worked at that university until February 1983. The author of over 170 journal and conference papers and four books has given invited lectures at over 80 universities and research institutes in Asia, Australia, Europe and North America. He was the Alexander-von- Humboldt Research Fellow (Germany) in 1983-84 and 1999, and a Visiting Professor at universities in Austria, Australia, Italy, Germany and the USA. His research interests include discrete-event computer simulation, performance modelling of multimedia telecommunication networks, on-line statistical analysis and modelling of teletraffic, and applications of experimental networking facilities.