In this paper, we present a framework for composing discrete-event simulation models from a large amount of airspace traffic data without using any specific waypoints. The framework consists of two parts. In the first part, abstracted route graphs that indicate representative routes in the airspace are composed. We propose two methods for extracting important routes in the form of graphs based on combination of various technologies such as space partition, trajectory clustering, and skeleton extraction. In the second part, discrete-event simulation models are composed based on statistical information on flight time along each edge of the abstracted route graph. The composed simulation models have intermediate granularity between micro models, such as multi-agent simulation, and macro models, such as queuing models, and therefore they should be classified as mesoscopic models. Finally, we show numerical results to evaluate the accuracy of the simulation model.

Boarding is the last step of aircraft turnaround and its completion in the shortest possible time is desired. In this paper, we propose a new boarding strategy that outperforms conventional strategies such as the back-to-front strategy and the outside-in strategy. The Steffen method is known as one of the most efficient boarding strategies in literature, but it is hard to be realized in the real situation because the complete sorting of passengers in a prescribed order is required. The proposed strategy shows a performance close to that of the Steffen method and can be easily implemented by using a special gate system.

This paper considers two simulation models for simple unreliable file systems with checkpointing and rollback recovery. In Model 1, the checkpoint is generated at a pre-specified time and the information on the main memory since the last checkpoint is back-uped in a secondary medium. On the other hand, in Model 2, the checkpointing is executed at the time when the number of transactions completed for processing is achieved at a pre-determined level. However, it is difficult to treat such models analytically without employing any approximation method, if queueing effects related with arrival and processing of transactions can not be ignored. We apply the generalized stochastic Petri net (GSPN) to represent the stochastic behaviour of systems under two checkpointing schemes. Throughout GSPN simulation, we evaluate quantitatively the maintainability of checkpoint models under consideration and examine the dependence of model parameters in the optimal checkpoint policies and their associated system availabilities.

This paper focuses on methodology underlying the application to fault tolerant computer systems with "no down communication" capability of stochastic Petri nets with general firing times. Based on a formal specification of the stochastic Petri net, we provide criteria for the marking process to be a regenerative process in continuous time with finite cycle-length moments. These results lead to strongly consistent point estimates and asymptotic confidence intervals for limiting system availability indices. We also show how the building blocks of stochastic Petri nets with general firing times facilitate the modeling of non-deterministic transition firing and illustrate the use of "interrupter input places" for graphical representation of transition interruptions.

Recent trends in down-sizing have resulted in the development of client server systems for many industries. This paper considers the application of stochastic Petri nets with general firing times for modeling of a concatenated client server system and the use of discrete-event simulation methods for stochastic Petri nets to study its behavior. This approach enables us to assess the most appropriate resource set of a concatenated client server system on the quantitative basis of the performability and the occurrence of system down conditions. Thus, system consultation, a new application of stochastic Petri nets, is presented.

The pursuit of higher availability has resulted in the development of fault tolerant systems for many industries. However, system characteristics that can be perceived by the customer have never been diagnosed quantitatively. This paper considers the application of stochastic Petri nets with general firing times to modeling of a fault tolerant system and the use of discrete-event simulation methods for stochastic Petri nets to study the behavior of the system. The stochastic Petri net model incorporates factors that compose the system as well as those that accompany it, including RAS characteristics of products, personnel arrangements, and system management. By modeling the behavioral aspect of each factor, it is possible to diagnose a fault tolerant system quantitatively on the basis of customer impact.