Using MBSE to Evaluate and Protect the Electrical Grid as a System of Systems

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.

Nowadays there is growing awareness of the importanceof Systems of Systems (SoS) which are large-scalesystems composed of complex systems. SoS possess specificproperties when compared with monolithic complex systems, inparticular: operational independence, managerial independence,evolutionary development, emergent behavior and geographicdistribution. One of the current main challenges is the impact ofthese properties on SoS security modeling and analysis. In thisresearch proposal, we introduce a new method incorporating aprocess, a language and a software architectural tool to model,analyze and predict security architectural alternatives of SoS.Thus security will be taken into account as soon as possible inthe life cycle of the SoS, making it less expensive

The exploration of Systems of Systems (SoS) modeling using Model‐Based Systems Engineering (MBSE) is an ongoing area of research, wherein researchers are actively investigating various frameworks and languages suitable for initiating SoS modeling. Urban Air Mobility (UAM) represents a novel approach to urban transportation, integrating multiple systems and stakeholders to enable on‐demand, environment friendly, efficient, and sustainable air travel within cities. International organizations have dedicated significant efforts to develop a comprehensive Concept of Operation (ConOps) for UAM, aiming to define the UAM ecosystem and identify the supporting systems. While previous research was focused on defining the Urban Air System (UAS) using Systems Modeling Language (SysML), there remains a gap in capturing the ConOps for UAM as a System of Systems (SoS) using SysML. This study seeks to address this gap by utilizing the MagicGrid Framework for SoS modeling.

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.

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

An increasing number of software systems today are systems of systems (SoS) comprising decentralized and heterogeneous systems with operational and managerial independence. The evolution of SoS is the rule and not the exception in practice due to frequently changing requirements, technologies, and markets. However, providing adequate support for the evolution of SoS is rather challenging as their behavior often emerges at runtime and is difficult to predict. Hence, SoS must be monitored during simulation and operation to ensure compliance with its requirements. In this position paper, we present challenges for SoS evolution from the domain of industrial automation. We discuss existing approaches supporting SoS evolution and derive research issues. We outline requirements for SoS evolution support and present key capabilities of a flexible monitoring and evolution infrastructure. We conclude with a discussion of research perspectives.

Summary form only given. The very label "critical infrastructure" implies that such systems are important. They are. Within the US alone, there are approximately 28,600 networked Federal Deposit Insurance Corporation (FDIC) institutions, 2 million miles of oil/gas pipelines, 2,800 power plants with 300,000 production sites, 104 nuclear power plants, 80,000 dams, 60,000 chemical plants, 87,000 food processing plants, and 1,600 water treatment plants. And, this is just part of our national infrastructure. Add to this telecommunications and other "everyday" utilities and the scope is enormous. Most of these systems, alone, would qualify as a network-centric system; that is, a system of systems (SoS) whose totality provides additional functionality over each of the aggregate systems - in other words, an SoS is truly greater than the sum of each of its parts. For example, in the electric power grid, a utility can trade power daily (even hourly) with its neighbors, thereby assuring its customers of continued service. This connectivity provides robustness of service; unfortunately, it also provides an access point for interdependency which can lead to a cascading failure, - "the domino effect" that was seen in the 14 August 2003 blackout and numerous other incidents. With the realization that most network-centric systems are critical comes the acceptance that we need to make these systems more "trustworthy". Given the complexity and scale of these systems, zero-defect software (while admirable) is a daunting goal. Trustworthiness, however, may be achievable. By trustworthiness we mean that "as humans" we expect that the "non-human system" will behave in some reliable, predictable form with "reasonable" recovery techniques when problems are encountered. This paper highlights the network-centric system attributes which should be considered in any integration effort, as well as commercial off-the-shelf (COTS) encapsulation techniques, and other engineering trade-offs in a large-scale design and development effort

Information Systems are viewed as a set of services creating a workflow of information directed to specific groups and members. This allows individuals to share ideas and their talents with other members. In such manner, tasks can be carried out both efficiently and effectively. Due to the nature of Information Systems that revolves around creating information useful to users, and in some higher forms of Information Systems creating knowledge, management of information and/or knowledge is part of their functionalities. In this paper we aim to study the placement of Information Systems as part of a System of Systems (SoS), as these large systems poses significant technical improvement in terms of information interoperability that overcomes conceptual and technical barriers. Therefore, we move towards defining and modeling System of Information Systems (SoIS). This paper discovers what is currently known about Information Systems and Systems of Systems, and proceeds towards suggesting an architecture of a System of Information Systems that integrates several Information Systems and allows information to be transferred at ease between those different components.

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.

Critical infrastructure (CI) resilience is the ability to prepare for disasters, manage disruptions, recover from them quickly, and absorb the lessons learned. Since CI consists of numerous systems of systems (SoS) that are managerially and operationally independent, their resilience is often difficult to maintain. The purpose of this paper is to describe an architecture that characterizes the resilience of SoS engineering (R-SoSE) processes for CI based on the contention that explicitly classifying the SoS can help systems engineers to better understand and practice R-SoSE processes. Focusing on the Japanese chemical industry, R-SoSE processes, including those of Japanese regulators, are described by Integration Definition 0 (IDEF0). Since CI behaviors are rule-based, the term "rules", characterized by laws and industry standards, are important R-SoSE process artifacts in this functional model. Two case studies are analyzed based on the taxa in ISO/IEC/IEEE 21841, which is the international standard for SoS taxonomy.

A System of Systems (SoS) is an arrangement of useful and independent sub-systems, which are integrated into a larger system. Examples are found in transport systems, nutritional systems, smart homes and smart cities. The composition of component sub-systems into an SoS enables support for complex functionalities that cannot be provided by individual sub-systems on their own. However, to realize the benefits of these functionalities it is necessary to address several software engineering chal-lenges including, but not limited to, the specification, design, construction, deployment, and management of an SoS. The various component sub-systems in an SoS environment are often concerned with distinct domains; are developed by different stake-holders under different circumstances and time; provide distinct functionalities; and are used by different stakeholders, which allow for the existence of conflicting requirements. In this paper, we present a framework to support management of emerging conflicting requirements in an SoS. In particular, we describe an approach to support identification of conflicts between resource-based requirements (i.e. requirements concerned with the con-sumption of different resources). In order to illustrate and evaluate the work, we use an example of a pilot study of an IoT SoS ecosystem designed to support food security at different levels of granularity, namely individuals, groups, cities, and nations.

System of systems (SoS) is an emerging field in the design and development of complex systems that are built from large scale component systems. A SoS has the following attributes: operational and managerial independence of components, a geographic extent that limits control mechanisms to information exchange, an evolutionary nature, and emergent behavior. The subsystems that comprise the SoS often are built by different organizations with conflicting goals, designed under different assumptions and built to different quality standards. These factors impact fault detection, fault isolation, and fault tolerance and can result in systems that cannot easily be debugged, integrated, or maintained. When fault detection and fault tolerance are deficient, the system may behave in a fragile or brittle manner, randomly and repeatedly crashing. Crashes prevent automated diagnosis algorithms from being executed and can prevent manual root cause analysis by erasing system state. Fragility during system integration can prevent achieving schedule milestones and deadlines. Deficient fault detection and fault isolation also impacts end users and system maintainers. (Think <insert name of infamous project here>).From the system architect's point of view, designing a system that can detect all possible fault conditions across all components can be an extremely difficult, if not impossible challenge. Can any system be trusted to diagnose or repair itself when it has been corrupted by faults? How do you prevent local faults from growing into global failures? The end users may have unreasonable expectations about how the system should behave when components within the SoS behave abnormally or fail. They may expect better behavior than the typical PC. The system maintainers may expect a coherent systems view of failures to isolate faulted components and to provide an orderly and safe shutdown or recovery.(Think power grid blackouts, Telecomm failures, etc.)The most beneficial way to achieve fault tolerance is to design in fault detection and fault reporting such that defined boundaries such as subsystems serve as natural firewalls for fault containment. Although partitioning the system into subsystems for fault containment is well known and practiced, the end result as experienced at the time of system integration is rarely a success. COTS middleware, intended to aid distributed design often becomes in effect a step backwards by providing fertile ground for faults and failures that breach fault containment boundaries. (Think <insert name of OS or middleware vendor here>)What can be done to improve this situation? This paper addresses the system architectural partitioning concept of the Coordinated Atomic Actions (CAA). CAA promotes a different manner of organizing software architecture that improves fault containment across potentially faulty components. CAA was first invented by members of Brian Randell's research group at the University of Newcastle at Tyne in the mid 1990's. CAA promotes the concept of the "transaction" which has been traditionally identified with database applications. When you access your bank account via ATM, you are exercising database transactions within your bank's financial SoS. CAA applies transactions to cooperating concurrent distributed processes, which are the basis for most large complex computing systems.

To meet increasing demand worldwide for electricity, efforts are underway to augment today's electrical grid infrastructure with enhanced information technology (IT), creating a Smart Grid capable of advanced monitoring, information exchange, analytics, and control. Because of the nature of the electrical grid, the stakeholders that control and use it, and the interconnectedness of proposed IT solutions, Smart Grid is a system-of-systems (SoS) that warrants new approaches to design. In this paper, the Relational-Oriented Systems Engineering and Technology Tradeoff Analysis (ROSETTA) Environment is assessed in light of Smart Grid system-of-systems (SoS) design. The specific example considered is a demand response (DR) problem of monitoring and leveling peak electricity demand. DR is first presented as an SoS design problem, comprising multiple, managerially independent systems (both human and technical) and subject to a variety of scenarios. Through discussion of the DR example, the intent and structure of ROSETTA is elucidated and initially considered for relevance to Smart Grid SoS design decisions.

This paper introduces a system of systems (SoS)-based perspective for critical infrastructure (CI) and derives implications for future development of the CI field. At a most fundamental level, CIs provide goods and services essential to public wellbeing. The importance of the CI field has never been more pronounced as the 21st century continues to unfold, beset by unprecedented levels of complexity, emergence, interdependence, and uncertainty. There are legions of threats to CIs and so too are the emerging and fragmented array of methods and tools to address different concerns within the field. This paper suggests that since SoS is concerned with integration and coordination of multiple systems to act in unison to achieve higher levels of performance, it offers a unique perspective on how we might address different concerns at systems level in the CI field. The paper examines that state of knowledge for the CI field and introduces an organizing construct within which the CI field might be framed.

While systems of systems (SoS) are starting to reach the market, it is not entirely evident how to analyze safety, and on a high level also security, of such systems. In fact, specific characteristics of SoS, such as independence, changing constitution, evolutionary development, and emergent behavior, provide certain challenges to the safety analysis. In this paper, such challenges are summarized and a systems theoretic safety analysis method, abbreviated as STAMP, is evaluated on an automotive SoS application example. In conclusion, STAMP seems well positioned to serve as a base for a future method for safety and, to a certain degree, security analysis of SoS, although some work remains to be done. The advantages and limitations of the STAMP approach when dealing with SoS are discussed.