Discrete Event System Specification Research Articles

The advances in the state of the art of modeling and simulation: Discrete event system specification (DEVS)

The advances in the state of the art of modeling and simulation: Discrete event system specification (DEVS)

Discrete Event System Specification Framework for Self-Improving Healthcare Service Systems

A healthcare service system (HSS) is made of humans and technology where for the foreseeable future, self-improvement will be primarily based on human understanding rather than machine learning. Therefore, for such a system to continually self-improve, it must provide the right data and models to support human decisions on selection of alternatives likely to improve the quality of its services. Our focus in this paper is to show how modeling and simulation (M&S) can help design service infrastructures that introduce coordination and bring into play the conditions for learning and continuous improvement. To do this, we discuss the application of the discrete event system specification (DEVS) formalism within system of systems engineering (SoSE) to develop coordination models for transactions that involve multiple disparate activities of component systems and that need to be selectively sequenced to implement patient-centered coordinated care interventions. We show how such coordination concepts provide a layer to support a proposed information technology for continuous improvement of healthcare as a learning collaborative system of systems (SoS).

A VR simulation framework integrated with multisource CAE analysis data for mechanical equipment working process

Nowadays, the virtual reality (VR) technology has been widely used in machinery to verify the working process and performance of equipment prototype in early design stage. To gain insight into the coupling of process verifying the timing and rhythm of equipment working and performance indicating the quality of equipment, a VR framework is proposed in this paper to integrate the modeling and simulation of working process with the visualization of multisource analysis data from various computer-aided engineering (CAE) software. The framework is equipped with an extended discrete event system specification (DEVS) method, named scripted DEVS, which divides the process modeling into two stages, namely, behavior modeling and data customization, and frees the mechanical designer from programming. Based on the method, a uniform procedure of data integration is designed to hide the specific structure and visualization implementation of diverse data from the modeler by a script format called PDTree (Process&Data Tree) and a series of visualization interfaces in model-view-controller (MVC) pattern. Three applications of different working processes are also presented finally to verify the flexibility and compatibility of the framework.

Co-simulation of cyber-physical systems using a DEVS wrapping strategy in the MECSYCO middleware

Most modeling and simulation (M&S) questions about cyber-physical systems (CPSs) require expert skills belonging to different scientific fields. The challenges are then to integrate each domain’s tools (formalism and simulation software) within the rigorous framework of M&S process. To answer this issue, we give the specifications of the Multi-agent Environment for Complex-SYstem CO-simulation (MECSYCO) middleware which enables to interconnect several pre-existing and heterogeneous M&S tools, so they can simulate a whole CPS together. The middleware performs the co-simulation in a parallel, decentralized, and distributable fashion thanks to its modular multi-agent architecture. In order to rigorously integrate tools that use different formalisms, the co-simulation engine of MECSYCO is based on the discrete event system specification (DEVS). The central idea of MECSYCO is to use a DEVS wrapping strategy to integrate each tool into the middleware. Thus, heterogeneous tools can be homogeneously co-simulated in the form of a DEVS system. By using DEVS, MECSYCO benefits from the numerous scientific works which have demonstrated the integrative power of this formalism and give crucial guidelines to rigorously design wrappers. We demonstrate that our discrete framework can integrate a vast amount of continuous M&S tools by wrapping the Functional Mockup Interface (FMI) standard. To this end, we take advantage of DEVS efforts of the literature (namely, the DEV&DESS hybrid formalism and Quantized State System (QSS) solvers) to design DEVS wrappers for Functional Mockup Unit (FMU) components. As a side-effect, this wrapping is not restricted to MECSYCO but can be applied in any DEVS-based platform. We evaluate MECSYCO with the proof of concept of a smart heating use case, where we co-simulate non-DEVS-centric M&S tools.

An integrative approach to simulation model discovery: Combining system theory, process mining and fuzzy logic

System inference, i.e., the building of system structure from system behavior, is widely recognized as a critical challenging issue. In System Theory, structure and behavior are at the extreme sides of the hierarchy that defines knowledge about the system. System inference is known as climbing the hierarchy from less to more knowledge. In addition, it is possible only under justifying conditions. In this paper, a new system inference method is proposed. The proposed method extends the process mining technique to extract knowledge from data and to represent complex systems. The modularity, frequency and timing aspects can be extracted from the data. They are integrated together to construct the Fuzzy Discrete Event System Specification (Fuzzy-DEVS) model. The proposed approach consists of three stages: (1) extraction of event logs from data by using the System Entity Structure method; (2) discovery of a transition system, using process discovery techniques; (3) integration of fuzzy methods to automatically generate a Fuzzy-DEVS model from the transition system. The last stage is implemented as a plugin in the Process Mining Framework (ProM) environment. A case study is presented in which Fuzzy-DEVS model is inferred from real life data, and the SimStudio tool is used for its simulation.

RPDEVS: Revising the Parallel Discrete Event System Specification

In this work, we present a Revised Parallel DEVS (RPDEVS) formalism. The Classic Discrete Event System Specification (DEVS) and Parallel DEVS (PDEVS) formalisms do not support modelling of ‘true’ mealy behaviour, i.e. reacting to an input message immediately with an output message. Instead, such behaviour has to be modelled via transitory states and multiple state updates. This not only increases model complexity, it also impedes reusability of model components in different contexts.RPDEVS enhances PDEVS with the capability to model mealy behaviour directly. Hence, the output function λ can access the input bag. This introduces some challenges regarding the simulation algorithm which we will take a look at.Further, the terms algebraic loop and illegitimate model will be discussed in the context of RPDEVS. It is shown that RPDEVS models which are free of algebraic loops are also legitimate. Finally, it will be demonstrated that like Classic DEVS and PDEVS, also RPDEVS provides closure under coupling.

BeeWS: honeybee-inspired, large-scale routing protocol for wireless sensor networks (WSNs)

Recently, scalable routing protocols using swarm intelligence (SI), which are designed and evolved for wireless sensor networks (WSNs), have become a research trend in literature. This paper presents an optimal method based on SI inspired by honeybees. This method has minimum energy consumption, self-organisation, and support for a large-scale, autonomous individuals that detect the best route. In this paper, we propose a new energy-aware, scalable, and robust routing algorithm called Bee wireless sensor (BeeWS) inspired by honeybee foraging behaviour. This study consists of three parts: (1) honeybee behaviours are modelled and these behaviours are adapted to the structure of WSN; (2) routing protocol criteria are determined using this model and (3) the developed model is tested in a simulation environment based on discrete event system specification (DEVS) in order to simulate and model WSN behaviours and compare to other SI based on WSN routing protocols.

Simulation of a Clustering Scheme for Vehicular Ad Hoc Networks Using a DEVS-based Virtual Laboratory Environment

Protocol design is usually based on the functional models developed according to the needs of the system. In Intelligent Transport Systems (ITS), the features studied regarding Vehicular Ad hoc Networks (VANET) include self-organizing, routing, reliability, quality of service, and security. Simulation studies on ITS-dedicated routing protocols usually focus on their performance in specific scenarios. However, the evolution of transportation systems towards autonomous vehicles requires robust protocols with proven or at least guaranteed properties. Though formal approaches provide powerful tools for system design, they cannot be used for every types of ITS components. Our goal is to develop new tools combining formal tools such as Event-B with DEVS-based (Discrete Event System Specification) virtual laboratories in order to design the models of ITS components which simulation would allow proving and verifying their properties in large-scale scenarios. This paper presents the models of the different components of a VANET realized with the Virtual Laboratory Environment (VLE). We point out the component models fitting to formal modeling, and proceed to the validation of all designed models through a simulation scenario based on real-world road traffic data.

<SUP align="right">DEVS</SUP>Server: ambient intelligence and DEVS modelling-based simulation server for epidemic modelling

To improve disease surveillance systems (DSS) with faster and accurate outbreak detection and epidemics propagation capabilities, the availability of fine-tuned models is required along with the design of server-based solutions that simulate the effects of public health authorities' measures and integrate ambient intelligence (AmI) capabilities to semantise epidemic models. Hosting discrete event system specifications (DEVS) models, these AmI servers and their communication protocols are different, miscellaneous and require interoperability. The triple-space computing (TSC) paradigm addresses interoperability by sharing information represented in a semantic format through a common virtual space. In this paper, we present DEVSServer, a fully distributed TSC simulation server solution (middleware) designed to meet the needs of parallel and distributed discrete event simulation. DEVSServer defines a service oriented architecture (SOA) interface for the TSC operations. This interface complies with DEVS formalism and focuses on simplicity, conviviality and modularity, so that a single or many simulations that support different models can still interact. To assess DEVSServer, we provide a tuberculosis epidemic model simulation in time-varying temporal network with genetic programming immunisation strategy approach.

MultiPDEVS: A Parallel Multicomponent System Specification Formalism

Based on multiDEVS formalism, we introduce multiPDEVS, a parallel and nonmodular formalism for discrete event system specification. This formalism provides combined advantages of PDEVS and multiDEVS approaches, such as excellent simulation capabilities for simultaneously scheduled events and components able to influence each other using exclusively their state transitions. We next show the soundness of the formalism by giving a construction showing that any multiPDEVS model is equivalent to a PDEVS atomic model. We then present the simulation procedure associated, usually called abstract simulator. As a well-adapted formalism to express cellular automata, we finally propose to compare an implementation of multiPDEVS formalism with a more classical Cell-DEVS implementation through a fire spread application.

Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation

Time is crucial in the airlines industry. Among all factors contributing to an aircraft turnaround time; passenger boarding delays is the most challenging one. Airlines do not have control over the behavior of passengers; thus, focusing their effort on reducing passenger boarding time through implementing efficient boarding strategies. In this work, we attempt to use cellular Discrete-Event System Specification (Cell-DEVS) modeling and simulation to provide a comprehensive evaluation of aircraft boarding strategies. We have developed a simulation benchmark consisting of eight boarding strategies including Back-to-Front; Window Middle Aisle; Random; Zone Rotate; Reverse Pyramid; Optimal; Optimal Practical; and Efficient. Our simulation models are scalable and adaptive; providing a powerful analysis apparatus for investigating any existing or yet to be discovered boarding strategy. We explain the details of our models and present the results both visually and numerically to evaluate the eight implemented boarding strategies. We also compare our results with other studies that have used different modeling techniques; reporting nearly identical performance results. The simulations revealed that Window Middle Aisle provides the least boarding delay; with a small fraction of time difference compared to the optimal strategy. The results of this work could highly benefit the commercial airlines industry by optimizing and reducing passenger boarding delays.

Development of stratified approach to software defined networks simulation

The stratified approach to software defined networks simulation has been proposed. It is based on Discrete Event System Specification formalism, atomic and coupled models concepts usage. The approach is aimed at simulation within the Windows environment, with an accent on the easiness of model reconfiguration. The proposed approach is also devoted to simulation-related overheads decrease. The atomic models of active (controller, switch, host) and passive (link) network components have been proposed. The coupled model of a software defined network comprising atomic models of active and passive components has been proposed. The estimations of the resulting coupled model complexity, with respect to the number of components basic atomic models, have been given. During experimentation, the pingall command usage scenario has been considered. For this purpose, the emulation via Mininet environment and the simulation on a basis of the proposed approach have been conducted. It has been shown that discrete-event simulation on a basis of the proposed approach is significantly less time-consuming. During the approach usage within the Windows environment, the absence of the need to utilize the Xming X Server and PuTTY utility for the purpose of visualization has been faced. The validity of the approach has been proven on a basis of the obtained experimental data. The adequacy of the resulting coupled simulation model of the network has been proven with t-criterion. The proposed approach can be used for the purpose of software defined networks validation with an accent on non-functional properties

Multiscale representation of simulated time

To better support multiscale modeling and simulation, we present a multiscale time representation consisting of data types, data structures, and algorithms that collectively support the recording of past events and scheduling of future events in a discrete event simulation. Our approach addresses the drawbacks of conventional time representations: limited range in the case of 32- or 64-bit fixed-point time values; problematic rounding errors in the case of floating-point numbers; and the lack of a universally acceptable precision level in the case of brute force approaches. The proposed representation provides both extensive range and fine resolution in the timing of events, yet it stores and manipulates the majority of event times as standard 64-bit numbers. When adopted for simulation purposes, the representation allows a domain expert to choose a precision level for his/her model. This time precision is honored by the simulator even when the model is integrated with other models of vastly different time scales. Making use of C++11 programming language features and the Discrete Event System Specification formalism, we implemented a simulator to test the time representation and inform a discussion on its implications for collaborative multiscale modeling efforts.

Improving Video Transmission in Cellular Networks with Cached and Segmented Video Download Algorithms

Satisfying the increasing demand for high data rates has become a main challenge for cellular network operators. Moreover, the demand for video traffic in cellular networks has been continuously increasing. In 2016, wireless video accounted for more than half of the total mobile data traffic, and it is expected to further increase in the upcoming years. This will increase the amount of data to be transmitted in cellular networks, and further increase the challenge for cellular network operators. Device-to-Device (D2D) communication, introduced by the Long Term Evolution-Advanced (LTE-A) standard, is a new communication technique that allows direct communication between devices in cellular networks without going through the Base-Station (BS). We present two algorithms for improving the throughput of video transmission in cellular networks. The algorithms are called Cached and Segmented Video Download (CSVD), and DIStributed, Cached, and Segmented video download (DISCS). The algorithms send segments of video files to selected User Equipments (UEs) in the cellular network, to cache and forward them to requesting UEs using D2D communication. We study the performance of both algorithms analytically in terms of the hit ratio. Furthermore, we use the Discrete EVent System Specification (DEVS) formalism to build an LTE-A network model and use the model to study the performance of CSVD and DISCS in terms of the cell’s aggregate data rate as well as the average data rate. Simulation results show that CSVD and DISCS achieve significant performance improvements in terms of the aggregate and average data rates.

A novel simulation method for power electronics: discrete state event driven method

In the analysis of power electronics system, it is necessary to simulate ordinary differential equations (ODEs) with discontinuities and stiffness. However, there are many difficulties in using traditional discrete-time algorithms to solve such equations. Kofman and others presented the quantized state systems (QSS) algorithm in the discrete event system specification (DEVS) formalism. The discretization is applied to the state variables instead of time range in QSS. QSS is efficient to solve ODEs, but it is difficulty to be used when simulating actual power electronics systems with controller’s and other events. Based on the idea of this numerical algorithm and discrete event, a Discrete State Event Driven (DSED) simulation method is presented in this paper, which is fit for simulation of power electronics system. The method is developed to deal with non-linearity, stiffness and multi-time scale of power electronics systems. The DSED simulation method includes event definition, module seperation and modeling, event-driven mechanisms, numerical computation based on QSS, and some other operations. Simulation results verified the effectiveness and validity of the proposed method.

Increasing the performance of a Discrete Event System Specification simulator by means of computational resource usage “activity” models

Domain-specific simulators often have an edge on general-purpose simulators in terms of performance. Their intricate knowledge of the domain allows them to aggressively optimize and take shortcuts. In contrast, simulators for more general formalisms, such as Discrete Event System Specification (DEVS), need to support a wider set of models. Their inability to use domain information prevents DEVS simulators from achieving as high performance as their domain-specific variants. To solve this problem, we introduce a way to enhance the simulation performance of DEVS models through the use of computational resource usage models, often termed “activity” models. These models augment general-purpose DEVS models with domain-specific information, which can be used by the simulator. We apply this information in the context of data structure optimization, load balancing, and model allocation. Activity-awareness is a non-invasive extension to the DEVS formalism, meaning that activity-augmented models remain perfectly valid for use in activity-unaware simulators. Similarly, models without activity can still be simulated by an activity-aware simulator. Our approach is validated by making PythonPDEVS, a Parallel DEVS simulator, activity-aware and evaluating the performance impact on a set of benchmark models.

Practical aspects of the DesignDEVS simulation environment

DesignDEVS is a simulation development environment based on the Discrete Event System Specification (DEVS) formalism. This paper provides an in-depth overview of the software while focusing on the practical considerations influencing its design. Practitioners who stand to benefit from systems engineering will approach formalism-based simulation tools with little knowledge of the underlying theory. It is therefore important that theoretical principles, such as the separation of model and simulator, be emphasized by the user interface. Other practical aspects of DesignDEVS include the simplicity of atomic model code, a focus on coupling for collaboration purposes, the enforcement of essential modeling constraints, and a reliance on best practices in cases where strict enforcement might inconvenience users. In DesignDEVS, an issue we refer to as the Insidious Pointer Problem is aggressively tackled through run-time error handling. By contrast, the separation of output values from state transitions is left as a best practice for the sake of user convenience. The design decisions explained in this paper are relevant to developers of other formalism-based tools seeking widespread adoption of scalable modeling and simulation practices.

Multi-Perspective Modeling of Healthcare Systems

This paper presents a multi-perspective approach to Modeling and Simulation (M&S) of Healthcare Systems (HS) such that different perspectives are defined and integrated together. The interactions between the isolated perspectives are done through dynamic update of models output-to-parameter integration during concurrent simulations. Most often, simulation-based studies of HS in the literature focus on specific problem like allocation of resources, disease propagation, and population dynamics that are studied with constant parameters from their respective experimental frames throughout the simulation. The proposed idea provides a closer representation of the real situation and helps to capture the interactions between seemingly independent concerns - and the effects of such interactions - in simulation results. The article provides a DEVS (Discrete Event System Specification)-based formalization of the loose integration of the different perspectives, an Object-Oriented framework for its realization and a case study as illustration and proof of concept.

Modeling and simulation of oncology clinic operations in discrete event system specification

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy under limited resources, such as nurses and chemotherapy chairs. Chemotherapy is a cancer treatment method that is administered orally or intravenously at an outpatient oncology clinic. Chemotherapy patients require a treatment regimen, which is a series of appointments over several weeks or months prescribed by the oncologist. The timing of these appointments is critical to the effectiveness of the chemotherapy treatment on cancer. This motivates the need for new methods for making efficient appointment schedules and for assessing clinic operation performance from both patient and management perspectives. This work uses a classic modeling approach based on systems theory to develop a discrete event system specification (DEVS) simulation model for oncology clinic operations called DEVS-CHEMO. DEVS-CHEMO is configurable to any oncology clinic and provides several capabilities for oncology clinic managers. For example, it can simulate scheduling of chemotherapy patients, clinic resources, and the arrival process of the patients to the clinic on the day of their appointment. This model simulates oncology clinic operations as patients receive chemotherapy treatments and thus allows for assessing scheduling algorithms using both patient and management perspectives. DEVS-CHEMO has been tested and validated using historical data from a real outpatient oncology clinic and the simulation results reported in this paper provide several insights regarding oncology clinic operations management.

Using the Parallel DEVS Protocol for General Robust Simulation with Near Optimal Performance

The Discrete Event Systems Specification (DEVS) formalism has been widely disseminated in this magazine and elsewhere for its applicability to computational science and engineering. While research in parallel and distributed simulation has been active in the past several decades, the utility of many techniques for high-performance DEVS simulation has been limited. Recent research has shown that that a reconstruction of Amdahl's and Gustafson's laws for parallelizing sequential code can afford a better understanding of the underlying principles and their application to simulation of DEVS models. In this article, the author shows, in comparison to the ideal case, that a relatively simple protocol based on the DEVS abstract simulator is both generally applicable and able to achieve significant speedup in parallel distributed simulation.