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2017 | Buch

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Guide to Modeling and Simulation of Systems of Systems

verfasst von: Prof. Bernard P. Zeigler, Hessam S. Sarjoughian

Verlag: Springer International Publishing

Buchreihe : Simulation Foundations, Methods and Applications

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This easy-to-follow textbook provides an exercise-driven guide to the use of the Discrete Event Systems Specification (DEVS) simulation modeling formalism and the System Entity Structure (SES) simulation model ontology supported with the latest advances in software architecture and design principles, methods, and tools for building and testing virtual Systems of Systems (SoS). The book examines a wide variety of SoS problems, ranging from cloud computing systems to biological systems in agricultural food crops. This enhanced and expanded second edition also features a new chapter on DEVS support for Markov modeling and simulation.

Topics and features: provides an extensive set of exercises throughout the text to reinforce the concepts and encourage use of the tools, supported by introduction and summary sections; discusses how the SoS concept and supporting virtual build and test environments can overcome the limitations of current approaches; offers a step-by-step introduction to the DEVS concepts and modeling environment features required to build sophisticated SoS models; describes the capabilities and use of the tools CoSMoS/DEVS-Suite, Virtual Laboratory Environment, and MS4 Me™; reviews a range of diverse applications, from the development of new satellite design and launch technologies, to surveillance and control in animal epidemiology; examines software/hardware co-design for SoS, and activity concepts that bridge information-level requirements and energy consumption in the implementation; demonstrates how the DEVS formalism supports Markov modeling within an advanced modeling and simulation environment (NEW).

This accessible and hands-on textbook/reference provides invaluable practical guidance for graduate students interested in simulation software development and cyber-systems engineering design, as well as for practitioners in these, and related areas.

Inhaltsverzeichnis

Frontmatter

Basic Concepts

Frontmatter

Chapter 1. Modeling and Simulation of Systems of Systems

Abstract

This book is about modeling and simulation in support “virtual build and test” of Systems of Systems (SoS) which include complex information-technology-based business, engineering, military systems, as well as the societal infrastructures they support. Such systems are at the root of this century’s global challenges of interacting economic crises, world-wide crop failures, extreme effects of climate change, and out-of-control viral epidemics. The book builds upon the material in the earlier books but goes beyond them in several critical ways. It centers on the unifying theme of “virtual build and test” as a means of integrating and providing context to the various technical concepts and tools discussed. In doing so, it provides an inclusive exposition of the many aspects of DEVS-based concepts and tools, all relating back to the “virtual build and test” theme. In particular, Chaps. 2–8 offer a step-by-step introduction to DEVS concepts and corresponding DEVS Modeling Environment (MS4 Me™) features that enable you to gain hands-on experience with the concepts to build sophisticated SoS models. A User Reference to the features of MS4 Me™ accompanies this book and is also sold by the publisher. The software itself is available from MS4 Systems (http://ms4systems.com). Chapters 9–12 develop more advanced concepts for modeling and simulation of SoS and illustrate them with MS4 Me™ features developed earlier. Chapters 13–18 discuss applications of the concepts to virtual build and test for a variety of SoS application domains using the capabilities of CoSMoS/DEVS-Suite and VLE as well as MS4 Me™.

Exercises to reinforce the concepts, to encourage using the three sets of tools, and to compare their capabilities are provided throughout the book. The primary target for this book is both practitioners and academics (professors and students). Practitioners include simulation software developers supporting system development, systems engineers designing and architecting systems, and managers of such projects. The technical level aimed at first- or second-year graduate students is augmented with introductory and summary sections that aim at the more general level so managers and others can skim over technical parts.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 2. DEVS Integrated Development Environments

Abstract

This book is divided into three parts. In the first part, we discuss basic DEVS and SES concepts and tools to support working with these concepts in the context of an actual modeling and simulation environment, called MS4 Modeling Environment (MS4 Me™). Then in Part II, we discuss more advanced concepts that such tools can support, and in Part III, we discuss some actual applications that throw light on the kinds of System of Systems problems that can be addressed with such concepts and tools.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 3. System Entity Structure Basics

Abstract

In this chapter, you will see how the System Entity Structure (SES) can help you construct models for Systems of Systems. In fact, we will use the SES to better understand the process for constructing such models. Modeling and Simulation (M&S) refers to a set of activities that are undertaken for a variety of reasons. We get a sense of the activities involved in M&S from a bird’s eye perspective before we dive down into DEVS-based tools for simulation model construction, the focus of this book. We formulate some of the basic activities in Modeling and Simulation as a process or sequence of steps that can be represented with a System Entity Structure. Besides conveying some familiarity with M&S activities, we use the example to discuss two unique features of the SES, decomposition and coupling.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 4. DEVS Natural Language Models and Elaborations

Abstract

MS4 Me^™ provides a primary means of creating simulation models through transformation of Finite Deterministic DEVS (FDDEVS) specifications. This chapter provides an understanding first, of the FDDEVS models, and second that how these files get transformed into DEVS atomic models expressed in Java. We then show how you can enhance FDDEVS models to enable to them to automatically generate DEVS atomic models in Java that have full capability to express messages and states. We also show how hierarchical models can be created using the Sequence Designer and then enhanced using the FDDEVS elaboration process.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 5. Specialization and Pruning

Abstract

A major strength of the SES is that it generates a family of hierarchical models rather than single composition. To understand how this is accomplished, we discuss a second main construct called specialization to complement and interact with the earlier introduced operation of decomposition. Specialization enables you to expand the alternatives, or options, for selection. We show how a pruning interface supports understanding the combinatorial space of possible selections. You need not make all available selections at one session and can return later to amend and add to a pruning file. This allows you to generate multiple possible Pruned Entity Structures that can be transformed into simulation models.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 6. Aspects and Multi-aspects

Abstract

This chapter starts with a discussion of how different aspects can be associated with the same entity and how this allows you to decompose a system in different ways. This leads to a consideration of the concept of multi-aspect which provides a uniform way to associate an unlimited number of related aspects with the same entity. Pruning a multi-aspect involves setting its multiplicity and restructuring it into an ordinary aspect with the specified number of components. We show how pruning of multi-aspects effectively open up a large space of simulation models with an unbounded variety of possibilities for coupling their components. Unfortunately, unless properly managed, this variety can also entail enormous amounts of detailed data entry which can be tedious and error prone. This leads to development of a uniform coupling rule which separates node-to-node network connectivity (specified by a directed graph) and port-to-port coupling which is forced to be uniform across all network connections. Some commonly employed schemes such as cyclic, cellular, and tree compositions have well-defined digraphs with uniform couplings so they fit this mold.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 7. Managing Inheritance in Pruning

Abstract

Pruning a System Entity Structure involves selecting aspects from entities as well as entities from specializations. In particular, selecting an entity (the child) from a specialization under another entity (the parent) results in a combination of child and parent that can inherit some of the properties of the parent or child. We show how MS4 Me^™ allows flexibility in how you want this inheritance to be carried out. The inheritance specifications are added to the pruning script and control the hierarchical model generated by transforming the pruning entity structure.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 8. Automated and Rule-Based Pruning and Experimental Execution

Abstract

The main features of the System Entity Structure, its specializations and aspects, as well as pruning and model generation have now been introduced. Such concepts provide a wealth and variety of potential hierarchical structures with which to tackle complex Systems of Systems problems. However, the rapidly growing combinatorial spaces that are set up by specialization and aspect selections can outstrip human capacity to do manual pruning. Accordingly, this chapter discusses automated pruning—concepts and tools for pruning that can reduce, and sometimes, eliminate, the manual pruning that is otherwise required. Enumerative pruning entirely eliminates manual pruning entirely but is restricted to small enough solution spaces. Random pruning samples from a large solution space to give a statistical picture of the space. Context-free and context-sensitive selection rules provide the ability to constrain the solution space to combinations that are more likely to meet your requirements. To conclude this chapter, we discuss a methodology and supporting concepts to create SES-based execution control of simulation models that lends itself to implementation on sequential computers as well as parallel and distributed platforms.

Bernard P. Zeigler, Hessam S. Sarjoughian

Advanced Concepts

Frontmatter

Chapter 9. DEVS Simulation Protocol

Abstract

One of the hallmarks of DEVS modeling and simulation is its fundamental separation of models from the simulation engines that execute them. The alternative, which is more common in today’s practice, is not to enforce such a clear separation and to indiscriminately mix constructs that relate to the model with those that relate to how it is being executed. This chapter discusses the fundamental separation of models from the simulation engines that execute them intrinsic to the DEVS framework. This leads to a layered architecture of modeling and simulation services that provides the basis for simulating DEVS coupled models that are created in a DEVS modeling environment. We use MS4 Me™ to describe the operation of the DEVS Simulation Protocol in terms of its interface requirements. We show how different implementations can satisfy the protocol using multi-aspects and uniform coupling patterns, which also illustrated the application of modeling concepts introduced earlier in the book. In addition, there is a discussion of how a typical event-based simulator can be simulated with the DEVS protocol and that casts light on the requirements for interoperability among DEVS and non-DEVS simulators.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 10. Dynamic Structure: Agent Modeling and Publish/Subscribe

Abstract

Dynamic structuring of models allows you to specify how models can change their structure during run-time. This chapter opens with a description of dynamic structure and its application to agent modeling. The Publish/Subscribe data distribution paradigm is described using dynamic structuring together with a Data Distribution Service that provides middleware based on this paradigm. We show how the DEVS Simulation Protocol for distributed simulation can be implemented in such middleware. We discuss how Publish/Subscribe topics support the exchange of DEVS Protocol commands and DEVS messages. We also discussed how topics that are individualized to components are not as desirable as those that can be subscribed to by all components. Insight into the choice of topics is gained by considering the all and each coupling of multi-aspects.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 11. Interest-Based Information Exchange: Mappings and Models

Abstract

In this chapter, we consider the application of MS4 Me™ to data engineering for complex data and interest-based data distribution in which data is targeted to the consumer’s interests. We discussed mappings of Pruned Entity Structures, in the form of XML documents, based on underlying System Entity Structures. Then we show how you can develop simulation models that implement such mappings and exchange XML documents in the manner of interest-based data distribution. Distributed simulation implementations that employ the DEVS protocol (Chap. 9) and data distribution services (Chap. 10) can deploy such models to provide the basis for information exchange based on the concepts of interest-based distribution.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 12. Languages for Constructing DEVS Models

Abstract

This chapter first provides a higher-level perspective on the approach that MS4 Me^™ takes to computational support for constructing DEVS models for virtual build and test. After describing this approach, we expand our view to examine whether Unified Modeling Language (UML) can provide a more expressive framework for DEVS specification. For completeness, we also look at how UML can serve as a target for implementation of DEVS models.

Bernard P. Zeigler, Hessam S. Sarjoughian

Applications

Frontmatter

Chapter 13. Flexible Modeling Support Environments

Abstract

In this chapter, we discuss a Modeling Support Environment (MSE) whose goal is to provide the flexibility to adapt its workflows, tools, and models, to diverse stakeholders. We outline the unique features of the MSE that support its use by a wide spectrum of potential users and developers of a system of fractionated spacecraft. These features include identification of user types to enable routing the user through relevant processing stages, automated generation of model artifacts adapted to selected pathways, conditioning of the solutions space to increase the opportunities to find suitable fractionated architectures, flexible simulation services, and consistent configuration across multiple abstraction models and semantics-based orchestration of service-oriented architecture. The approach taken in the design and development of the MSE is based on fundamental principles that have application much beyond spacecraft fractionated systems. This generic quality of the MSE concept suggests the applicability of DEVS Modeling Environments to virtual build and test of today’s system of systems.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 14. Service-Based Software Systems

Abstract

The goal of this chapter is to show the characteristics of service-based software systems as systems of systems, and how their simulation counterparts can be developed using a DEVS modeling approach. We show how standards such as Service-Oriented Architecture (SOA) play key roles in developing simulation models that are better equipped to be interchanged with their real counterparts. Generic SOA-compliant DEVS model components are developed to closely represent their real counterparts and are used to develop simulation instances of real service-based software systems. Users can systematically and efficiently prototype service-based software systems in simulated settings with capability to evaluate their quality of service attributes such as timeliness and accuracy.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 15. Cloud System Simulation Modeling

Abstract

A set of services form a system of services, a set of hardware parts form a system of networked components, and the former and latter together form cloud systems. This chapter shows how simulations for cloud system designs can be succinctly characterized in a DEVS Modeling Environment which supports software–hardware co-design. This enables trade-off analyses among alternative architectural designs that exhibit new kinds of inherent complexity that are impractical to stage in real-world settings. An example uses a voice communication system which exhibits features that are common to numerous cloud systems. Using SOA-compliance, the formulation becomes independent of any specific application and this supports developing simulation models for different domains of interest. The simulation platform also can be used with actual services and adapts itself during run-time using dynamic structure capability (Chap. 14). It can be combined with actual cloud systems which can support evaluating system structure scalability and operational efficiency using timeliness and accuracy attributes. Such an environment makes cloud system simulation an attractive, useful tool for early cloud system co-designs and evaluations.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 16. Model Development and Execution Process with Repositories, Validation, and Verification

Abstract

Model Development and Execution Process with Repositories, Validation, and Verification In this chapter, we discuss another modeling and simulation environment that supports both development and storage of families of DEVS models for Systems of Systems. Component-based System Modeler (CoSMo) is grounded in a unified logical, persistence, and visual model development concept. We show how you can develop; store, retrieve, and instantiate DEVS SoS models such as those for service oriented and cloud systems (Chaps. 14 and 15). We develop a unified concept supporting logical, visual, and persistence modeling and simulation framework (CoSMoS) which lends itself for data (XML Schema) modeling and XML Schema code as well as cellular automata modeling. We show how the concept of SW/HW co-design for systems of systems fits seamlessly into the CoSMoS framework. While being based on the same underlying concepts of DEVS model construction, MS4 Me™ and CoSMoS offer somewhat different perspectives on support for SoS model construction.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 17. Modeling and Simulation of Living Systems as Systems of Systems

Abstract

In this chapter, we show that the system theoretic basis of the DEVS formalism matches the systemic point of view adopted in the living sciences field. Two examples, one in animal epidemiology and the other in plant growth modeling, illustrate different characteristics of DEVS and its extensions. We show how these multi-formalistic abilities of DEVS Modeling Environments are very promising to help answer critical issues regarding natural risk management and poverty reduction. We show how DEVS can serve as a universal formalism for living dynamical system modeling and simulation. However, DEVS is an abstract formalism and can be hard to manage when the modeling effort has to focus on the application domain. So the Virtual Laboratory Environment (VLE) provides an environment where DEVS is used at the simulation level but where the modeling level is composed by a set of specialized modeling components, where components are represented by appropriate formalisms. In this way, the modeler can design the model using the most suitable formalism, or coupling several ones, without any knowledge of DEVS. VLE supplies the mappings into DEVS of the main formalisms used in living system modeling and simulation. We show how the tackling of urgent issues, such as the economical and ecological crises, diversity erosion, or poverty, will be based on creative compositions of shared representations among multiple discipline-based experts. These shared models will embed heterogeneous knowledge elements at different scales, i.e., in heterogeneous formalisms. For these reasons, simulation models for living systems, viewed as systems of systems, are best formalized with DEVS and its extensions.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 18. Activity-Based Implementations of Systems of Systems

Abstract

A System of Systems (SoS) is a composition of component systems and is naturally modeled as a DEVS coupled model which is the computerized representation to support “virtual build and test.” However, given that SoS refers to something existing in the real world, there is also an implementation model, a model that reflects more about the characteristics of the environment in which the SoS will live. This chapter presented activity concepts as a means to bridge the gap between information-level requirements (behavior and timing) and energy consumption in the implementation. This bridge enables implementations of SoS that minimize energy while meeting information-level requirements. In particular, we show how hardware synthesis from DEVS coupled models can exploit disparity in the activity level of its components, giving rise to design for low-power optimization methods. The basic approach is a globally asynchronous, locally synchronous design pattern that enables efficient clock management and clock gating of individual design elements. Explicitly capturing timing requirements within the system model enables optimization to create a design that differentially assigns clock frequencies. This allows component clocks to run only when needed and at frequencies that may be much less then would be needed in the standard single clock design. A DEVS-based hardware implementation of an SoS can exploit the timing requirements and achieve significantly lower power consumption than conventional approaches.

Bernard P. Zeigler, Hessam S. Sarjoughian

Chapter 19. DEVS Support for Markov Modeling and Simulation

Abstract

Markov Modeling is among the most commonly used forms of model expression. Besides their general usefulness, the Markov concepts of stochastic modeling are implicitly at the heart of most forms of discrete-event simulation. This chapter, an addition to the second edition, shows how such concepts are fully compatible with the DEVS characterization of discrete-event models and a natural basis for the extended and integrated Markov Modeling facility developed within the MS4 Me environment. The facility described here offers an easy-to-use set of tools to develop Markov models which are full-fledged DEVS models and able to be integrated with other DEVS models just like other DEVS models. Due to their transition structure, Markov models can be individualized with specific transition probabilities/rates which can be changed during model execution for dynamic structural change. Finally, we discuss case studies where such modeling can provide significant insights through multi-resolution modeling in drug therapy and how speedup using parallel processing is limited by the interprocessor connection network. An appendix gives some background for this chapter on exponential distributions, Poisson processes, and Markov basics.

Bernard P. Zeigler, Hessam S. Sarjoughian

Backmatter

Titel: Guide to Modeling and Simulation of Systems of Systems
verfasst von: Prof. Bernard P. Zeigler
Hessam S. Sarjoughian
Verlag: Springer International Publishing
Electronic ISBN: 978-3-319-64134-8
Print ISBN: 978-3-319-64133-1
DOI: https://doi.org/10.1007/978-3-319-64134-8