No abstract

Restart is a common technique for improving response-times in complex systems where the causes of delays can either not be discerned, or not be addressed by the user. With restart, the user aborts a running job that exceeds a deadline, and resubmits it to the system immediately. In many common scenarios, this approach can reduce the response-times that the user experiences. Restart has been well-studied for scenarios where only one user applies restart, and typically in cases where queueing effects can be neglected. In this paper we approach the question of restart in a scenario where restart is applied by many users in a system that can be modelled as an open queueing network. We apply the GNetworks formalism to this problem. We use negative customers to model the abortion and retry of a request. The open G-network uses multiple classes with phase-type distributed service times. This allows the approximation of a preemptive repeat different behaviour as it is natural for multiple restarts of a request. We compute the response time of a request and show that an optimal restart interval can be found. The results are compared with simulation.

In this paper we analyze the quality of wireless data transmission. We are primarily interested in the importance of the distance between sender and receiver when measuring data loss rate and the length of lossy and loss-free periods. The ultimate purpose of this type of study is to quantify the effects of mobility. We have sampled data and find that distance certainly is an important indicator but the loss rate of packets is also determined by other factors and does not always monotonically increase with the distance. We further find that while the distribution of the length of lossy periods mostly shows an exponential decay the distribution of the length of loss-free periods does not even always monotonically decrease. Both, the packet loss probability and the distribution of the length of loss-free periods can be well represented using probabilistic models. We fit simple Gilbert-Elliot models as well as phase-type distributions to the data using different fitting tools and provide loss models that can easily be used in simulation and testbed studies.

No abstract

In this paper we will present a simplified approach for extracting the ground level -a digital terrain model (DTM) -from the surface provided in a digital surface model (DSM). Most existing algorithms try to find the ground values in a digital surface model. Our approach works the opposite direction by detecting probable above ground areas. The main advantage of our approach is the possibility to use it with incomplete DSMs containing much no data values which can be e.g. occlusions in the calculated DSM. A smoothing or filling of such original derived DSMs will destroy much information which is very useful for deriving a ground surface from the DSM. Since the presented approach needs steep edges to detect potential high objects it will fail on smoothed and filled DSMs. After presenting the algorithm it will be applied to a test area in Salzburg and compared to a terrain model freely available from the Austrian government.