Nil H. Kilicay-Ergin

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.

Model Based Systems Engineering for System of Systems Using Agent-Based Modeling

Abstract Model Based Systems Engineering (MBSE) follows a model centric approach in contrast to the traditional document centric approach. The complexity of SoS development lends itself nicely to a model centric approach, especially a model that can represent the independence of the systems that comprise the SoS. An agent-based model provides a framework where the SoS and each system are independent entities with individual dynamics and interactions. The System of Systems (SoS) development depends on contributions from the individual systems each having their own agenda and priorities. System-to-system interactions are often necessary to accomplish the overall objectives and capabilities of the SoS. This research investigates the SoS development of an Acknowledged SoS with its associated individual systems and represents this development in an Agent-Based Model (ABM). The ABM includes decision models for the individual system agents that capture system dynamics and system-to- system negotiations as well as system to SoS negotiations. The ABM incorporates the key factors that influence SoS and individual systems’ dynamics and enables systems engineers to try different scenario inputs and analyze the overall dynamics.

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 Decision Analysis in Negotiation between the System of Systems Agent and the System Agent in an Agent-Based Model

Previous papers have described a computational approach to System of Systems (SoS) development using an Agent-Based Model (ABM). This paper describes the Fuzzy Decision Analysis used in the negotiation between the SoS agent and a System agent in the ABM of an Acknowledged SoS development. An Acknowledged SoS has by definition a limited influence on the development of the individual Systems. The individual Systems have their own priorities, pressures, and agenda which may or may not align with the goals of the SoS. The SoS has some funding and deadlines which can be used to negotiate with the individual System in order to illicit the required capability from that System. The Fuzzy Decision Analysis determines how the SoS agent will adjust the funding and deadlines for each of the Systems in order to achieve the desired SoS architecture quality. The Fuzzy Decision Analysis has inputs of performance, funding, and deadlines as well as weights for each capability. The performance, funding, and deadlines are crisp values which are fuzzified. The fuzzified values are then used with a Fuzzy Inference Engine to get the fuzzy outputs of funding adjustment and deadline adjustment which must then be defuzzified before being passed to the System agent.

Modeling system of systems acquisition

System of systems (SoS) acquisition is a dynamic process of integrating independent systems. This paper describes modeling of the SoS acquisition environment based on the Wave Process Model. Agent-based modeling methodology is utilized to abstract behavioral aspects of the acquisition process.

Incentive-Based Negotiation Model for System of Systems Acquisition

Lack of collaboration between individual systems and system of systems (SoS) program management is identified as one of the leading problems in SoS acquisition. This is especially a major concern in acknowledged SoS where a designated SoS program management has no authority over the constituent systems. Therefore, it is important to consider mechanisms to persuade individual systems to participate in the SoS development. In SoS where individual systems have their own self-interests, negotiation becomes an important mechanism to increase participation in SoS development. Another mechanism, incentives, is used in a wide range of applications to improve performance and collaboration. In this paper, an incentive based negotiation model is outlined as a mechanism to increase participation of individual systems into the SoS development. The negotiation model is integrated into an SoS Engineering and Architecting multilevel model referred to as Flexible & Intelligent Learning Architectures for SoS (FILA-SoS). Various aspects of SoS acquisition are modeled in the FILA-SoS including SoS meta-architecture generation, evaluation as well as negotiation between SoS and individual systems. Individual systems exhibit behaviors, ranging from selfish to cooperative. The negotiation model is demonstrated on an SoS engineering application: Intelligence, Surveillance, and Reconnaissance (ISR) SoS acquisition case where a desired meta-architecture is selected for negotiation, and incentives are determined for systems based on deviation from the desired meta-architecture quality. The analyses of the results from this application domain provide insights into how incentives can be used by decision makers to increase participation in SoS engineering and development.

Agent-based Modeling of Dynamic Pricing Scenarios to Optimize Multiple-generation Product Lines with Cannibalization

Abstract In todays market, companies tend to develop long-term multiple-generation product strategies instead of releasing consecutive single products to maintain market competitiveness. Even though this strategy affords market vitality, it also can bring about inter-product-line cannibalization. Cannibalization within a multiple-generation product line is a complex problem, and it has seldom been explored. It indeed is a critical subject that companies need to take into account at the product line planning stage in order to ensure their long-term profitability. In this study, we view a multiple-generation product line as a complex adaptive system, and propose a new model that can simulate the potential cannibalization scenarios within a multiple-generation product line. The model concentrates on the price variations over time for every single generation of product in a multiple-generation product line and is built upon an agent-based-methodology. Every product generation in the product line is regarded as an independent agent, and is authorized to adjust its sales price according to the shifts in the market demand. The proposed model can assist companies in developing appropriate dynamic pricing strategies at the early product line planning stages.

Improving Collaboration in Search and Rescue System of Systems

Abstract Lack of collaboration between individual systems and System of Systems (SoS) program management is identified as one of the leading problems in SoS engineering. In SoS where individual systems have their own interests, it is necessary to incorporate mechanisms to persuade individual systems to participate in the SoS development. In this paper an incentive based negotiation model is outlined as a mechanism to increase participation of individual systems into the Search and Rescue SoS development. The model takes into account variations in outcomes due to uncertainty in the acquisition environment as well as contribution of each system to overall SoS mission. Different levels of individual system effort and different levels of SoS outcome are identified to determine appropriate levels of incentives for individual systems. Study of this application domain provides insights into how incentives can be used by decision makers to increase participation in SoS engineering and development.

An Online Graduate Requirements Engineering Course

Requirements engineering is one of the fundamental knowledge areas in software and systems engineering graduate curricula. Recent changes in educational delivery and student demographics have created new challenges for requirements engineering education. In particular, there is an increasing demand for online education for working professionals. This paper describes a graduate requirements engineering course designed to address these new dynamics while aligning learning objectives with the prevailing body of knowledge and professional practices.