This book describes the classical smoothing, filtering and prediction techniques together
with some more recently developed embellishments for improving performance within …

Solving sparse systems of linear equations is at the heart of scientific computing. Large
sparse systems often arise in science and engineering problems. One such problem we …

This paper describes symbolic techniques for the construction, representation and analysis
of large, probabilistic systems. Symbolic approaches derive their efficiency by exploiting …

Power management in battery operated sensor networks, is a hot topic addressed by many
ongoing researches. One of the most commonly employed technique consists in turning on …

We study a Markovian agent-based model (MABM) in this paper. Each agent is endowed
with a local state that changes over time as the agent interacts with its neighbours. The …

Computer systems are ubiquitous in almost all spheres of our life, motivating the need for
them to function correctly and in a timely manner. Continuous time Markov chains (CTMCs) …

We propose a unified framework to represent a wide range of continuous-time discrete-state
Markov processes on networks, and show how many network dynamics models in the …

There are widely used analysis techniques for stochastic Petri nets with phase type (PH)
distributed firing times. These techniques are based on the generation of an expanded …

The application of theoretical scheduling approaches to the real world quite often crashes
into the need to cope with uncertain events and incomplete information. Stochastic …

Implicit techniques for construction and representation of the reachability set of a high-level
model have become quite efficient for certain types of models. In particular, previous work …