http://www.hurray.isep.ipp.pt Abstract: Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

For industrial environments it is true that Ethernet technologies are there to stay. In fact, a number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor applications. Fullduplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional field bus networks? Fieldbus fundamentalists often argue that the two things are not comparable. In fact, Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. Where are the higher layers and the application enablers that permit building real industrial applications? And, taking for free that they are available, what is the impact of those protocols, mechanisms and application models on the overall performance of Ethernet-based distributed factory-floor

Virtual Reality (VR) has grown to become state-of-theart technology in many businessand consumer oriented E-Commerce applications. One of the major design challenges of VR environments is the placement of the rendering process. The rendering process converts the abstract description of a scene as contained in an object database to an image. This process is usually done at the client side like in VRML[1] a technology that requires the client’s computational power for smooth rendering. The vision of VR is also strongly connected to the issue of Quality of Service (QoS) as the perceived realism is subject to an interactive frame rate ranging from 10 to 30 frames-per-second (fps), real-time feedback mechanisms and realistic image quality. These requirements overwhelm traditional home computers or even high sophisticated graphical workstations over their limits. Our work therefore introduces an approach for a distributed rendering architecture that gracefully balances the workload between the client and a clusterbased server. We believe that a distributed rendering approach as described in this paper has three major benefits: It reduces the clients workload, it decreases the network traffic and it allows to re-use already rendered scenes.

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be. A Few What-Ifs on Using Statistical Analysis of Stochastic Simulation Runs to Extract Timeliness Properties Nuno Pereira1, Eduardo Tovar1, Berta Batista1, Luis Miguel Pinho1, Ian Broster2 1Polytechnic Institute of Porto, Porto, Portugal, 2University of York, York, UK {npereira, emt, bbatista, lpinho}@dei.isep.ipp.pt; ianb@cs.york.ac.uk