Louis Pape

A Fuzzy Evaluation method for System of Systems Meta-architectures☆

Abstract A method is proposed for evaluating a range of System of Systems (SoS) meta-architecture alternatives. SoS are composed through combination of existing, fully functioning Systems, possibly with minor functional changes, but certainly by using the combined Systems to achieve a new capability, not available from the Systems alone. The meta-architecture describes how all possible subsets of Systems can be combined to create an SoS. The fitness of a realizable SoS architecture may be characterized by terms such as unacceptable, marginal, above average, or excellent. While these terms provide little information about the SoS when used alone and informally, they readily fit into fuzzy membership sets that overlap at their boundaries. More descriptive attributes such as “ease of use,” which might depend on individual user and a set of conditions, “mission effectiveness” over a particular suite of missions, and “affordability,” which may change over time with changing business climate, etc., lend themselves readily to fuzzy evaluation as well. An approach to defining the fuzzy concepts and establishing rule sets to provide an overall SoS evaluation for many sets of participating individual Systems represented by the meta-architecture is discussed. An application of the method is discussed within the framework of developing and evaluating a hypothetical Intelligence, Surveillance and Reconnaissance (ISR) SoS capability.

Understanding System of Systems Development Using an Agent-Based Wave Model

Abstract System of Systems (SoS) development is a complex process that depends on the cooperation of various independent Systems [1] . SoS acquisition and development differs from that typical for a single System; it has been shown to follow a wave paradigm known as the Wave Model [2] . Agent based models (ABMs) consist of a set of abstracted entities referred to as agents, and a framework using simplified rules for simulating agent decisions and interactions. Agents have their own goals and are capable of perceiving changes in the environment. Systemic (global) behavior emerges from the decisions and interactions of the agents. This research provides a generic model of SoS development with a genetic algorithm and fuzzy assessor implemented in an agent based model. The generic SoS development follows the Wave Model. The genetic algorithm provides an initial SoS meta- architecture. The fuzzy assessor qualitatively evaluates SoS meta-architectures. The agent-based model implements the generic SoS development, the genetic algorithm, the fuzzy assessor, and independent SoS and system agents and shows the SoS development based on an initial set of conditions. A prototype model is developed to test the concept on a sample from the DoD Intelligence, Surveillance, and Reconnaissance (ISR) domain.

Multi-agent Based Architecture for Acknowledged System of Systems☆

Abstract Negotiation and collaboration issues in large organizations, with centralized control, across the globe, are becoming more complex with each passing day. The Acknowledged System of Systems (SoS) is a new approach that addresses some of these issues in a systematic, efficient manner. This paper proposes a hierarchical architectural framework to support Acknowledged SoS architecting and analysis for a Department of Defense (DoD) Acquisition process. A major challenge of the successful planning and evolution of an Acknowledged SoS is the lack of understanding of the impact of presence or absence of a system and its interface with another constituent system on the overall architecture. The agent based model (ABM) structure developed here provides Acknowledged SoS manager that has both ability to address the managerial issues as well as a decision making tool for SoS architecting. This paper offers a complete integration of the techniques used to represent SoS architectures. The work illustrates the modeling approach through a domain setting.

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

Abstract Acknowledged systems of systems (SoS) lie on a continuum between authoritarian central control and anarchy. The constituent systems are independent, with a life and purpose of their own. The systems require not only technical interfaces, but also social interactions, to create the SoS. A fuzzy optimization process may be used to select a desirable SoS configuration, but it may be unachievable due to the inability to persuade the systems to cooperate in the plan. Modeling the systems’ internal decision processes could help understand how to design better SoS architectures. This research used generic, modular modeling processes to examine two proposed SoS architectures and the impact of degree of cooperation on the suitability of the achieved SoS.

A Hybrid Genetic Algorithm and Particle Swarm Optimization with Type-2 Fuzzy Sets for Generating Systems of Systems Architectures☆

Abstract Both modeling and simulating a system of systems (SoS) are difficult due not only to a changing environment but also the unique behavior that is linked to different participating systems. Generating architectures for a SoS is a multi-objective optimization problem with large number of variables and constraints. The paper presents several of computational intelligence techniques that can generate SoS architectures, such as genetic algorithms (GA), and particle swarm optimization (PSO) combined with Type 2 Fuzzy logic nets. The Maritime search and rescue (SAR) was used as a SoS domain scenario to both implement and demonstrate the architecting methodology. SAR utilizes a variety of systems, including unmanned aerial vehicles (UAV), coordination command control, communication systems and other larger manned vessels. The proposed methodology delivers SoS architects of SAR missions the ability to exploit the interdependence among all systems as well as individual systems inherent characteristics to satisfy stakeholders’ desired attributes. The architect is thus able to design architectures that are robust, efficient, net-centric, and affordable.

Assessing Robustness in Systems of Systems Meta-architectures☆

Abstract New Systems of Systems (SoSs) are frequently created through partial participation from independent, existing systems with their own continuing missions. These systems’ contribution to the SoS may be contingent on changing priorities and conditions. Therefore, when devising a SoS architecture, consideration should be given to the SoS robustness to occasional lack of availability of individual systems. Robustness is generally the ability to deliver capability in unknown future conditions. Not knowing which systems will be present would seem to fit this definition for a SoS. A fuzzy approach to defining SoS performance in terms of capabilities provided by each type of system and interfaces, with the robustness defined by the remaining performance when one system is absent, is proposed. Several types of capabilities are typically available from several systems when putting together an SoS. An ideal SoS architecture, while paying due homage to lean principles and affordability, should also avoid single point failures. When a suitable SoS performance model exists, the architect can assess SoS capability measures of performance changes when each individual system is removed. Even low fidelity performance models can help distinguish among alternative SoS architectures. Testing architecture models for robustness can improve overall understanding of the SoS capabilities, and selecting architectures for more distributed performance increases robustness.

Selecting Attributes, Rules, and Membership Functions for Fuzzy SoS Architecture Evaluation☆

Abstract The development of the FILA-SoS meta-architecture approach to acknowledged systems of systems (SoS) analysis allows a relatively unbiased method for exploring a potential SoS architecture space. This paper delves more deeply into the process of building the lists of desirable fuzzy attributes of a SoS, developing rules for combining attribute values to an overall assessment, and discovering membership function shapes that work well. A wide range of options exist for all the individual elements of SoS assessment. Some recommendations for finding an appropriate combination for the adjustable parameters of fuzzy assessment models through random architecture chromosome testing and iteration are developed.