This paper describes modeling discrete event systems in Metropolis using one of the key concepts employed by Metropolis, orthogonalization of design aspects, which in this particular case, is the orthogonalization between capability and cost. To support the orthogonalization, quantity annotation mechanism is introduced. This paper formally analyzes simulation strategies for quantity annotation ...

Studies of memory T cell differentiation are hampered by a lack of quantitative models to test hypotheses in silico before in vivo experimentation. We created a stochastic computer model of CD4+ memory T cell generation that can simulate and track 10(1)-10(8) individual lymphocytes over time. Parameters for the model were derived from experimental data using naive human CD4+ T cells stimulated ...

Analytical methods in reliability analysis are useful for studying simple problems. For complex networks with cross-linked (non-series/parallel) component configurations, it is difficult to use mathematical reliability analysis. Powerful methods for reliability analysis of such systems have been developed using discrete event simulation. The main drawback of these methods is that they are compu...

This paper presents a component-based modeling technique for systems with continuous and discrete dynamics. It uses hierarchical composition to hide the implementation details of one component from other components, and keeps the components at the same level of hierarchy interacting under a well-defined model of computation. Continuous time, discrete event, and finite state machine models are c...

Logical process (LPs) is a widely used modeling paradigm in parallel discrete-event simulation (PDES). However, there is a lack of effective methods for formalizing the LP-based modeling of PDES. This situation obstructs the unambiguous and platform-independent description of the LP-based model. To solve this problem, in this work, a formalism named Partitioned Event Graph (PEG) is presented. P...

In order to make it possible to effectively represent deterministic uncertainties and vagueness as well as the human subjective observation and judgement inherent to many real-world problems, especially those in biomedicine, we introduce, in this paper, fuzzy states and fuzzy events and generalize (crisp) discrete event systems (DES) to fuzzy DES. The largely graph-based current framework of th...

This paper presents a crisis response simulation model architecture combining a discrete-event simulation (DES) environment for a crisis scenario with an agent-based model of the response organization. In multi-agent systems (MAS) as a computational organization, agents are modeled and implemented separately from the environmental model. We follow this perspective and submit an architecture in ...

Optimizing system resource utilization is a key design objective for system engineers in communications, electronics, and other industries. System resources such as processors, memory, or bandwidth on a communication bus are often shared by various components in the system. To understand the utilization of a shared resource, system engineers must do two things: identify constraints on the resou...

In parallel discrete event simulation, a run in which events are executed at each object according to their timestamp is a correct run (i.e., it satisses causal-ity). In such a run, the execution order of events at any object corresponds to the total order imposed on them by timestamps. In this paper we introduce the notion of weak causality between simulation events. Such a relation deenes a p...

The diagnosis of a discrete-event system is finding out whether the behavior of the system is normal or faulty, given observations of this behavior. We show how the diagnosis problems can be translated into the propositional satisfiability problem (SAT) and then solved by the state-of-the-art SAT algorithms. Our experiments demonstrate that the SAT algorithms are able to deal with the problems,...