Speeding up the simulation of discrete-event wafer fab models is essential because optimizing the scheduling and dispatching policies under various circumstances requires repeated evaluation of the decision candidates during parameter-space exploration. In this paper, we present a runtime abstraction-level conversion approach for discrete-event wafer-fabrication (wafer-fab) models to gain simulation speedup. During the simulation, if a machine group of the wafer fab models reaches a steady state, then the proposed approach attempts to substitute this group model with a mean-delay model (MDM) as a high abstraction level model. The MDM abstracts the detailed operations of the group's sub-component models into an average delay based on the queueing modeling, which can guarantee acceptable accuracy under steady state. The proposed abstraction-level converter (ALC) observes the queueing parameters of low-level groups to identify the convergence of each group's work-in-progress (WIP) level through a statistical test. When a group's WIP level is converged, the output-to-input couplings between the models are revised to change a wafer-lot process flow from the low-level group to a mean-delay model. When the ALC detects a divergence caused by a re-entrant flow or a machine-down, the high-level model is switched back to its corresponding low-level group model. The ALC then generates dummy wafer-lot events to synchronize the busyness of high-level steady state. The proposed method was applied to case studies of wafer-fab systems and achieves simulation speedup from 6.1 to 11.8 times with corresponding 2.5 to 5.9% degradation inaccuracy.

The simulation speedup of designed RTL NoC regarding the packet transmission is essential to analyze the performance or to optimize NoC parameters for various combinations of intellectual-property (IP) blocks, which requires repeated computations for parameter-space exploration. In this paper, we propose a high-level modeling and simulation (M&S) approach using a revised cellular automata (CA) concept to speed up simulation of dynamic flit movements and queue occupancy within target RTL NoC. The CA abstracts the detailed RTL operations with the view of deciding a cell's state of actions (related to moving packet flits and changing the connection between CA cells) using its own high-level states and those of neighbors, and executing relevant operations to the decided action states. During the performing the operations including connection requests and acceptances, architecture-independent and user-developed routing and arbitration functions are utilized. The decision regarding the action states follows a rule set, which is generated by the proposed test environment. The proposed method was applied to an open-source Verilog NoC, which achieves simulation speedup by approximately 8 to 31 times for a given parameter set.

Due to the significant growth of the demand for data-intensive computing, in addition to the emergence of new parallel and distributed computing technologies, scientists and domain experts are leveraging languages specialized for their problem domain, i.e., domain-specific languages, to help them describe their problems and solutions, instead of using general purpose programming languages. The goal of these languages is to improve the productivity and efficiency of the development and simulation of concurrent scientific models and systems. Moreover, they help to expose parallelism and to specify the concurrency within a component or across different independent components. In this paper, we introduce the concept of domain-specific flowbased languages which allows domain experts to use flow-based languages adapted to a particular problem domain. Flow-based programming is used to support concurrency, while the domain-specific part of these languages is used to define atomic processes and domain-specific validation rules for composite processes. We propose a modeling language that can be used to develop such domain-specific languages. Since this language allows one to define other languages, we often refer to it as a meta-modeling language.

Hajj is one of the largest mass gatherings where Muslims from all over the world gather in Makah each year for pilgrimage. A mass assembly of such scale bears a huge risk of disaster either natural or man-made. In the past few years, thousands of casualties have occurred while performing different Hajj rituals, especially during the Circumambulation of Kaba (Tawaf) due to stampede or chaos. During such calamitous situations, an appropriate evacuation strategy can help resolve the problem and mitigate further risk of causalities. It is however a daunting research problem to identify an optimal course of action based on several constraints. Modeling and analyzing such a problem of real-time and spatially explicit complexity requires a microscale crowd simulation and analysis framework. Which not only allows the modeler to express the spatial dimensions and features of the environment in real scale, but also provides modalities to capture complex crowd behaviors. In this paper, we propose an Agent-based Crowd Simulation & Analysis framework that incorporates the use of Anylogic Pedestrian library and integrates/interoperate Anylogic Simulation environment with the external modules for optimization and analysis. Hence provides a runtime environment for analyzing complex situations, e.g., emergency evacuation strategies. The key features of the proposed framework include: (i) Ability to model large crowd in a spatially explicit environment at real-scale; (ii) Simulation of complex crowd behavior such as emergency evacuation; (iii) Interoperability of optimization and analysis modules with simulation runtime for evaluating evacuation strategies. We present a case study of Hajj scenario as a proof of concept and a test bed for identifying and evaluating optimal strategies for crowd evacuation

The High-Level Architecture (HLA) is the de-facto standard in simulation interoperability. This paper presents a possible way for HLA to integrate with a service-oriented architecture (SOA) in the context of a smart building project. The paper discusses the design of an HLA federate for the inclusion of a service oriented smart building controller in the simulation loop.

The rapid adoption of service-oriented architecture (SOA) in many large-scale distributed applications requires the development of adaptive service-based software systems (ASBS) with the capability of monitoring the changing system status, analyzing, and controlling tradeoffs among various quality-of-service (QoS) aspects, and adapting service configurations to satisfy multiple QoS requirements simultaneously. In this paper, our results toward the development of adaptive service-based software systems are presented. The formulation of activity-state-QoS (ASQ) models and how to use the data from controlled experiments to establish ASQ models for capturing the cause-effect dynamics among service activities, system resource states, and QoS in service-based systems are presented. Then, QoS monitoring modules based on ASQ models and SOA-compliant simulation models are developed to support the validation of the ASBS design. The main idea for developing QoS adaptation modules based on ASQ models is discussed. An experiment based on a voice communication service is used to illustrate our results.

It is common practice to build complex systems from disparate sub-systems. Model composability is concerned with techniques for developing a whole model of a system from the models of its sub-systems. In this paper we present a new kind of multi-formalism modeling composability framework which introduces the concept of knowledge interchange broker for composing disparate modeling formalisms. The approach offers separation of concerns between model specifications and execution protocols across multiple modeling formalisms. The framework is exemplified via vehicle and agent models described in the discrete-event system specification and reactive action planning formalisms. A high-level software specification that illustrates an implementation of this framework is described. Ongoing and future research directions are also briefly presented.

Successful development of large-scale complex and distributed real-time systems commonly relies on models developed separately for simulation studies and software implementation. Systems theory provides sound modeling principles to characterize structural and behavioral aspects of systems across time and space. The behavior of these models can be observed using simulation protocols that can correctly interpret time-based logical dynamics. Similarly, object-orientation theories and software architecture principles enable modeling static and dynamic behavior of systems. While models described either in system-theoretic or object-orientated languages may be used for both software design and simulation modeling, each has its own strengths and weaknesses. For example, a class of system-theoretic modeling approach called Discrete-event System Specification (DEVS) provides an appropriate basis to develop simulation models exhibiting concurrent and distributed behavior. Similarly, the Unified Modeling Language with real-time (UML-RT) constructs can be used to develop software design models that can be implemented and executed. Since software models are not suitable to be used as simulation models and simulation models may not adequately lend themselves to serve as software design blueprints, it is important to examine these approaches. We show some of the key shortcomings of these simulation and software design modeling approaches by developing some detailed specifications and implementation of a coffee machine with a focus on their treatment of logical and physical time.

An approach to modeling and simulating distributed object computing systems as a set of software components mapped onto a set of networked processing nodes is presented. The modeling approach has clearly separated hardware and software components enabling systems level, distributed codesign engineering. The distributed codesign engineering refers to a system-theoretic approach to concurrent hardware and software systems engineering that provides a tractable method for analyzing the inherent complexities that arise in distributed computing systems. A software abstraction forms a distributed cooperative object (DCO) model to represent interacting software objects. A hardware abstraction forms a loosely coupled network (LCN) model of processing nodes, network gates and interconnecting communication links. The distribution of DCO software across LCN processors forms an object system mapping (OSM). This OSM provides a sufficient specification to allow simulation investigations. In simulation, the behavioral dynamics of the interacting DCO software components load and compete for LCN processing and networking resources. The LCN resource constraints thus impose performance constraints on the interactions of the DCO software objects. Class models of the DCO, LCN, and OSM component structures and behavior dynamics were formally characterized using the discrete event system specification (DEVs) formalism. These class model specifications were implemented in DEVSJAVA, a Java implementation of DEVS. Class models of experimental frame components were developed and implemented to facilitate analysis of the interdependent distributed system behaviors during simulations. Our DEVS-DOC M&S environment enables distributed systems architects, integration engineers and system designers to analyze performance and examine engineering trades of system structures, topologies and technologies. A case study demonstrates the ability to model and simulate a real world system and the complex interactions that arise in distributed computing systems.

In this paper the design and implementation of Distributed Real-Time DEVS/CORBA is discussed as an extension of previously developed DEVS-based modeling and simulation frameworks. The major objective in developing Distributed Real-Time DEVS/CORBA is to establish a framework in which the distributed real-time systems can be designed through DEVS-based modeling and simulation studies, and then migrated with minimal additional effort to be executed in the real-time distributed environment. This environment will provide generic support for developing models of distributed embedded software systems, evaluating their performance and timing behavior through simulation and easing the transition from simulation to actual executions In this paper we describe detailed design and implementation aspects of the environment which was implemented over Visibroier CORBA middleware and ACE/TAO real-time CORBA services.

In this paper, we present two specifications, scalable DEVS specification and distributed container object specification, to support scalability and interoperability of DEVS-based modeling and simulation (M and S) systems. The scalable DEVS specification lists a set of interfaces which create and simulate DEVS models, and control simulation activities among simulators. The distributed container object specification provides a heterogeneous and distributed collection framework focusing on ensemble operations. The proposed specifications contain a rich set of both data and operations which are necessary for building scalable M and S environments that should provide invariance in both performance and quality of service of a system as the size, complexity, and interdependence of its elements increases. We describe design and implementation aspects of those specifications.

The paper proposes a layered architectural framework to support agent based system development in a collaborative, multidisciplinary engineering setting. This architecture is viewed from two distinct perspectives. First, the environment must enable agent based modeling and simulation. Second, it should support concurrent (team oriented) engineering. The main focus is on the proposed layered architecture delineating various needs of an agent based system, thus supporting incremental specification design, implementation, and testing. In our discussions, we distinguish between performing agents and simulated agents. The former refers to agents as they are performing their tasks in real-world settings. The latter refers to agents that have their behavior simulated in a virtual environment. In these terms, the proposed framework is intended to form the basis for environments that support development of agents, in both performance and simulation modes, as well as in hybrid combination (both performing and simulated agents interacting at the same time). The proposed framework is a step toward realization of agent based systems under the umbrella of the simulation based acquisition (SBA) initiative of the US Department of Defense.

Perceiving agents have a limited sensitivity to distinguish input stimuli. Whatever the cause random noise, limited numbers of sensing elements, intentional desensitization formulation of such behavioral phenomena at the system level has not attracted much interest. This work is a first attempt to formalize the limited-sensitivity abstraction and to explore its implications for systems modeling and simulation, both conceptual and practical. In this article, a system theoretic formalization of perceiving agents called quantized systems is provided, linking them with discrete event modeling paradigms and exploring their approximation capability and message reduction in distributed simulation.