Simulating systems of systems using situation/reaction paradigm

In the twenty-first century, mission success will require unprecedented interoperability among disparate constituent systems resulting in a System of Systems (SoS). Unlike traditional systems engineering where systems are created based on a set of user needs, a SoS is composed of multiple constituent systems, at various stages within their lifecycles (i.e. new start systems, systems in-development, legacy systems), to satisfy needed mission capabilities. System of Systems Engineering has been exploring appropriate methods and processes for almost two decades. This paper takes the discussion further by introducing a System of Systems Engineering and Integration (SOSE&I) methodology. SoSE&I is the planning, analyzing, and integrating of constituent systems into an SoS capability greater than the sum of those individual systems. The SoSE&I "Vee" process model is introduced and discusses how it is used to engineer the SoS throughout its lifecycle to increase systems integration and interoperability, and directly impact the operational success.

Systems of Systems (SoS) are complex systems composed of managerially and operationally independent constituent systems (CS). Smart cities are examples of SoS. However, these types of systems impose challenges to traditional software architecture such as highly evolutionary architecture due to the evolution of individual CS and emergent behaviors that results from the interoperability of CS. Executable Models (ExM) are a class of models that can be executed and that can assist on architectural design of SoS. By using them, architects can predict the SoS structure and behavior by visualizing and simulating the SoS still at design-time. On the other hand, as any other emergent technologies, it suffers with absent scientific evidences of its benefits, mainly in industrial context. The main contribution of this master thesis project intends to be the presentation of evidences about the use of ExM to solve problems in the SoS software architecture design. For achieving such purpose, this project is structured in well-defined steps: (i) a systematic mapping study, (ii) elaboration of a conceptual map derived from the mapping study, (iii) a survey to obtain perceptions from software engineering professionals on the use of ExM in the context of engineering simple systems and (iv) a new survey expanding the previous study and to obtain perceptions from software engineering professionals on the use of ExM in the context of architectural design of SoS. Preliminary results reveal that ExM have been reported in diverse SoS domains, offering a dynamic and interactive view to the SoS. We also found that software engineering professionals see ExM as suitable solution for dealing with complex and critical systems as SoS.

In traditional Systems Engineering, the Systems Engineer acts as the overall system creator. Primarily through stakeholder interaction, requirements analysis, and architectural design, the Systems Engineering shapes and influences the system solution through specifications, top-down design, and bottoms-up integration and test. With the large-scale introduction of commercial-off-the-shelf (COTS) components, the Systems Engineer acts more like a composer. The top-down requirements and design activities need to be adjusted to account for the bottoms-up constraints imposed by the COTS technology. The System Engineer shapes and influences COTS-based developments through requirements modifications and negotiations, along with simultaneous system design, integration, and test. This paper explores the changing role of the Systems Engineer in today's complex system of systems (SoS) environment. We will use the analogies of conductor and choreographer to describe the System Engineering leadership challenges that exist in a SoS environment. Similar to a conductor, we will look at the set of activities that ensure the elements in the SoS work together in harmony. Similar to a choreographer, we will look at the set of activities that ensure the expressive nature of each of the SoS elements is fully realized, while still conforming to its overall objectives. Using these analogies, we will draw some conclusions for the evolving Systems Engineering role in a SoS environment. We will also explore which of these activities emerge as dominant in situations both with and without a lead SoS integrator.

Advances in technology have made it easy to integrate multiple modern systems to form complex system‐of‐systems (SoS) to achieve unparalleled levels of functionality that are otherwise not achievable by the constituent systems in isolation. In fact, with the recent explosion of machine learning techniques to build autonomous systems such as drones and self‐driving cars, there is a pressing need to ensure that they collaboratively and safely operate in an SoS context. However, in general, the characteristic emergent behaviors of complex SoS – that directly impact its operational measures of success or Measures of Effectiveness (MOEs) – is very difficult, if not impossible, to manually explore, anticipate, and arbitrate just from knowledge of its underlying systems. Further, there are multiple scenarios of evolution in such complex SoS, including evolution in the emergent behavior of the SoS. The continuous, continual, and evolving nature of the SoS and constituent system environment's state and possible actions, adds further complexity. In this paper, we present a novel approach that leverages Reinforcement Learning, a machine learning approach, to inculcate adaptable intelligence in constituent systems to adapt their behaviors in tandem with the evolution of emergent behavior at the SoS level. By augmenting the reward mechanism of RL by leveraging SoS‐Constituent System MOE Relationship, that relates and ranks System MOEs vs. SoS MOEs, we inculcate an Intelligent‐Behavior Evolution Agent, with the necessary constraints to learn to maximize the SoS and system‐level MOEs, while adapting itself to the evolution in SoS. We illustrate our approach and demonstrate its feasibility and potential by applying it to a power grid SoS case example. The effectiveness and performance of the approach are quantified.

In systems engineering (SE) activity in System of Systems (SoS), Enterprise Systems Engineering (ESE), and Complex Systems Engineering (CSE) continues to increase. There is controversy as to how well conventional methods of SE are able to handle our most difficult complex systems problems, and whether new ways of systems thinking will help. This tutorial will: 1) explain and give examples of complex systems and CSE; 2) review related definitions and terminology; 3) present CSE principles to create mindsets that will accelerate progress in your application domains; 4) provide tools for characterizing SE environments and what is being doing about it; and 5) suggest a methodology for CSE. Teamed class exercises will stimulate creative thought and interactions among participants. The presentation materials and accompanying discussions should deepen our understanding of SE and better prepare us for future SE endeavors.

This paper is concerned with the engineering of systems that are themselves comprised of other component systems, and where each of the component systems serves organizational and human purposes.i¾ i¾ These component purposes may be locally managed and optimized independently, or nearly so, of the objectives to be met by the composite system.i¾ i¾ There are a number of inherent characteristics of these systems, and such related terms as systems of systems (SOS) or federations of systems (FOS) or federated systems of systems (F-SOS) are often used to characterize them.i¾ i¾ It is asserted that the resultant systems generally possess the characteristics of complex adaptive systems.i¾ i¾ We provide an overview of the literature describing these engineering efforts and provide plausible strategies for systems engineering and management of SOS and FOS that are based on the principles of a 'new federalism'.i¾ i¾ Finally, the implications of these plausible SOS and FOS systems engineering and management concepts are discussed with emphasis on evolutionary acquisition in the style of DoD and Intelligence Community related programs.

A System of Systems (SoS) is a large-scale complex system composed of Constituent Systems (CSs) that interact organically to achieve SoS level goals that cannot be achieved by individual CSs. Various uncertainties may arise in SoS in addition to the uncertainties of each CS. Uncertainty in SoS may cause it to fail in various situations. To debug these failures efficiently, a high-quality fault knowledge base is needed for the SoS. However, existing studies assume that (1) there are sufficient data when creating an initial fault knowledge base and that (2) various uncertainties related to the characteristics of the SoS cannot be considered. Therefore, this study proposes an approach to create a fault knowledge base in SoS that considers uncertainty and then determines the quality of fault data so as to build a high-quality fault knowledge base for SoS. The proposed approach categorizes faults based on the nature of uncertainty and the manifestation location, making it possible to find and add fault types that are currently not considered. Through a case study of an Advanced Driver Assistance System (ADAS), we followed the process domain experts use to create a fault knowledge base. Extracting and classifying knowledge from more than 9,000 fault data entries revealed that only 7 out of 10 fault types were observed. The proposed approach could successfully find unknown faults that were not in the generated fault knowledge base.

This article describes the emerging roles of the systems engineering (SE) function in supporting enterprise management in information‐intensive organizations. “Enterprise Systems Engineering” (ESE) comprises three major roles or “levels” of systems engineering for successful and efficient development or procurement of large complex systems of systems (SoS). While the authors' experience focuses predominantly on government organizations acting as their own SoS integrators, the SoS ESE concept has generic applicability for any organization, public or private, seeking to attain competitive advantage through leveraging of information technology resources and systems. The processes and tools described here have been developed and successfully employed to facilitate government project management and investment decisions and control. [Carlock and Decker, 1998] This paper describes a formal three‐level SoS ESE process that, at the top level, organizes and maintains all of the details of the enterprise‐wide SoS architecture and strategic development plan in a flexible framework that accommodates the changes expected over a long SoS evolution. The information maintained in this framework allows the organization to know where it is going, how and when it is going to get there, the required capabilities and interfaces of each SoS component, and the impact of changes to system requirements, budgets, schedules, etc., on the overall SoS. The middle level processes allow the organization to perform trade studies among alternative solutions to implement required capabilities based on what is best for the enterprise‐wide SoS rather than just local considerations. The end result of the middle level processes is a selected and approved solution and its associated cost, schedule, benefits, and technical baselines. The third level processes implement the approved solutions in accordance with the approved baselines. © 2001 John Wiley & Sons, Inc. Syst Eng 4: 242–261, 2001

Systems of Systems (SoS) modeling is becoming increasingly important in both civilian and military systems. The Department of Defense (DoD) Defense Acquisition Guidebook, [1] defines a SoS as a “set or arrangement of systems that results when independent and useful systems are integrated into a larger system that delivers unique capabilities.” Organizations are changing their emphasis from “We need a new system” to “We need to achieve a specific outcome.” As these outcomes become more complex and the associated systems more complex, the management, modeling and simulation of these SoS becomes equally challenging. Often, the SoS is modeled in all its complexity, often at a single level of abstraction or level of detail. Instead of a “megamodel” approach, a standards-based “model of models” approach is what is necessary. This approach will use the Object Management Group (OMG) Unified Profile for DoDAF and MODAF (UPDM) for modeling enterprise architectures from capabilities to detailed components, and the Reusable Asset Specification (RAS) for defining reusable assets. Combining UPDM and RAS provides a Model of Models approach with the main model specifying assets in various levels of details. The models specified by these assets can be referenced when detailed analysis is required, or hidden when a SoS viewpoint is required, allowing the analyst to see the forest through the trees. The paper will also include an assessment of the applicability and effectiveness of this approach. The International Conference on Systems Engineering (INCOSE) System of Systems Working Group (SoSWG) has collected a set of “Pain Points on SoS” from a variety of international sources. This paper will review these pain points and discuss how the application of a Model of Model approach, combined with standards-based modeling tools and a reusable assets approach can help to alleviate some of the pain currently being felt by SoS architects and managers. Hopefully, this response to their SOS will deliver some much-needed assistance.

: A major challenge to the successful planning and evolution of an acknowledged System of Systems (SoS) is the current lack of understanding of the impact that the presence or absence of a set of constituent systems has on the overall SoS capability. Since the candidate elements of an SoS are fully functioning, stand-alone Systems in their own right, they have goals and objectives of their own to satisfy, some of which may compete with those of the overarching SoS. These system-level concerns drive decisions to participate (or not) in the SoS. Individual systems typically must be requested to join the SoS construct, and persuaded to interface and cooperate with other Systems to create the new capability of the proposed SoS. Current SoS evolution strategies lack a means for modeling the impact of decisions concerning participation. The goal of this research is to model the evolution of the architecture of an acknowledged SoS that accounts for the ability and willingness of constituent systems to support the SoS capability development. Since DoD Systems of Systems (SoS) development efforts do not typically follow the normal program acquisition process described in DoDI 5000.02, the Wave Model proposed by Dahmann and Rebovich is used as the basis for this research on SoS capability evolution. The Wave Process Model provides a framework for an agent-based modeling methodology, which is used to abstract the non-utopian behavioral aspects of the constituent systems and their interactions with the SoS. In particular, the research focuses on the impact of individual system behavior on the SoS capability and architecture evolution processes. A proof of concept agent-based model (ABM) of the system interactions is developed and integrated with a genetic algorithm (GA) to explore the potential architectural design space, using a fuzzy associative memory (FAM) to evaluate candidate architectures for simulating SoS creation and evolution.

This describes a system of systems (SoS) systems engineering (SE) artifacts, compares and contrasts them with similar ones developed and used for individual systems, and explains how they are used to guide SoS engineering processes. This concludes with next steps for using SoS artifacts to continue maturing the understanding of SoS SE in an international cooperative effort with the United Kingdom, Australia, and Canada.

A System-of-Systems (SoS) is a collection of distributed independent individual systems that interact with one another to achieve an SoS capability requirement that cannot be achieved by individual systems alone (in contrast, in a monolithic system, hardware or software components are integrated to form a single entity). Interdependency between SoS systems, while enabling new capability, also means that failures can cascade throughout the SoS, creating development delays or additional system failures. Here we develop a method based on Bayesian networks to evaluate the resilience of SoS design alternatives to failures during operations. We propose a conditional resilience metric that measures each constituent system's contribution to overall SoS resilience, and a resilience pattern that shows how SoS performance degrades as systems fail. SoS resilience is determined by both the SoS architecture and the constituent system reliability. In a simple example based on the Littoral Combat Ship SoS, we determine the two most critical systems using the conditional resilience metric. Adding a communications link between these two systems increases the resilience, resulting in higher expected performance and slower expected performance degradation as a result of system failure. The conditional resilience and resilience pattern can be used by designers and other decision makers to identify SoS architectures and systems that increase SoS resilience to failure.

Littoral combat is a critical component of naval warfare that has gained importance since the late 20th century due to a shift from matched blue-water combat to agile, asymmetric warfare near the coast. With the increased relevance of this type of naval combat, the ability of a networked naval warfare System-of-Systems (SoS) to operate effectively given the challenges of operations in the littoral zone becomes imperative. Resilience in an SoS in the face of a variety of threats is vital. These threats may take various forms: traditional warfare, cyber attacks, or communications breakdowns. The challenge for any SoS practitioner is identifying such architectures from a vast design space. We define an architecture as the constituent systems in the SoS and the connections among these systems. We seek to apply an agent-based modeling approach to create an architecture evaluation tool that leverages the modular nature of an SoS to quickly conduct trade studies and analyses to identify architectures that are resilient to a variety of threats. The simulation tool is built on the principles of the Open Systems Architecture put forth by the Department of Defense (DoD). We present an analysis that seeks to find a suitable SoS architecture configuration that maintains operability and performance during the loss of command authorities. This loss can be attributed to battle casualties or other forms of threats including communications failures. We demonstrate that distributing managerial control in the architecture improves, to some extent, SoS performance in terms of time to threat elimination. This single analysis demonstrates how SoS practitioners can use agent-based models to quickly construct and evaluate potential architectures against a variety of threats and disruptions, ultimately building resilient SoS architectures that perform to prescribed levels even in the face of network failures and attacks.

Fuzzy Optimization of Acknowledged System of Systems Meta-architectures for Agent based Modeling of Development

Through the increasing complexity and dynamics of industrial automation scenarios, the notion of Systems of Systems (SoS) has gained importance in this field. Here, interconnected constituent (hardware as well as software) systems collaborate in order to achieve common goals and to increase the efficiency of certain industrial applications.The Arrowhead Tools project aims at proposing a comprehensive, flexible platform for supporting SoS engineering in its every phase, in the form of an engineering toolchain. Thereby, although the SoS operation aspect has been already elaborated on, the design phase and the usage of design artifacts as part of a continous tool interoperability scenario received less attention so far. In this paper, we describe such a toolchain interoperability scenario, paving the way towards an established, integrated solution, by linking systems modeling practices with SoS operational management. In particular, we propose a customtailored abstract SysML profile for Arrowhead SoS design, and a prototype implementation for a bidirectional link between SoS models and a tool for managing Arrowhead SoS via a customtailored textual format. We illustrate the approach through a realistic industrial application.