Dawn A. Trevisani

The Stability Model: An Interactive Framework for Measuring Robustness and Resiliency in Military Command and Control Systems

The increasing complexity and tight coupling between people and technology in military Command and Control C2 systems has led to greater vulnerability due to system failure. Although system vulnerabilities cannot be completely eliminated, the accidental or anticipated failures have to be thoroughly understood and guarded. Traditionally, the failure in C2 systems has been studied with resiliency and the concept of self-healing systems represented with reactive models or robustness and the concept of self-protecting systems represented with proactive models. The authors propose the stability model for simultaneous consideration of robustness and resiliency in C2 systems. Robustness and resiliency are measured with multiple criteria i.e. repair-recovery times and repair-recovery costs. The proposed interactive framework plots the robustness and resiliency measures in a Cartesian coordinate system and derives an overall stability index for various states of the C2 system based on the theory of displaced ideals. An ideal state is formed as a composite of the best performance values and a nadir state is formed as a composite of the worst performance values exhibited by the system. Proximity to each of these performance poles is measured with the Euclidean distance. The C2 system should be as close to the ideal state as possible and as far from the nadir state as possible. The stability index is a composite measure of distance from the ideal and nadir states in the C2 system. The authors present a case study at the Air Force Research Laboratory to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.

The fuzzy stability model: an interactive framework for measuring robustness and resiliency under uncertainty

The increasing complexity in workflow management systems WMSs has led to greater vulnerability due to system failure. Although system vulnerabilities cannot be completely eliminated, the accidental or anticipated failures have to be thoroughly understood and guarded. Traditionally, the failure in military command and control C2 systems has been studied with robustness, the concept of self-protecting systems and resiliency, the concept of self-healing systems. Robustness and resiliency in C2 systems are generally measured with precise repair-recovery costs and repair-recovery times. However, the repair-recovery costs and repair-recovery times in real-world problems are often imprecise or uncertain. Fuzzy logic and fuzzy sets can represent imprecise or uncertain information formalising inaccuracy in human decision-making. We develop a stability model for simultaneous consideration of robustness and resiliency in fuzzy C2 systems. We measure robustness and resiliency with fuzzy repair-recovery times and fuzzy repair-recovery costs. The interactive method plots the fuzzy robustness and fuzzy resiliency measures in a Cartesian coordinate system and derives an overall fuzzy stability index for various processes in the C2 system based on the theory of displaced ideals.

A deterministic risk analysis and measurement model for assessing availability and integrity in command and control systems

Military command and control (C2) systems are increasingly challenged by a host of modern problems, namely, internal vulnerabilities and external threats. Several approaches have been suggested in the literature to measure availability and integrity in C2 systems. Despite the importance of developing and maintaining self-protecting and self-healing processes, the simultaneous consideration of availability and integrity has received little attention in the literature. We propose a deterministic quantitative risk analysis and measurement (Q-RAM) framework for C2 systems which is focused on the failure risk induced by internal vulnerabilities and external threats present in the C2 systems. The proposed system allows risk managers to get a comprehensive snapshot of the system availability and integrity, assess the failure risks with the assistance of a multi-factor risk metric, and manage those risks by searching for the best combination of countermeasures, allowing the user to determine the preferred tradeoff between the systems availability and integrity costs.

Incorporating realistic command, control, and communications (C3) effects in military mission level simulation

The Joint Synthetic Battlespace for Research and Development (JSB-RD) program is performing research and development in the areas of Modeling and Simulation (M&S), advanced visualization and analysis, and Decision Support. The goal of this work is to create a robust environment for use in ongoing research efforts in areas including Information Fusion, Effects Based Operations, and Predictive Battlespace Awareness. Present day mission level simulations suffer from overly simplistic, inaccurate communication link models that significantly overestimate available in-theater communications, a vital enabler of Command, Control and Communications (C3). Predictions based from such models can, and generally do, substantially differ from those encountered under actual battle conditions. In an effort to improve the accuracy and reliability of mission level simulation predictions, JSB-RD is adding detailed military link models into their core environment, along with the necessary logic to properly address C3 effects within the synthetic world. This paper chronicles these JSB-RD efforts to date. This paper first presents a high level view of the JSB-RD project, followed by a detailed discussion of current efforts to enhance simulation predictions accuracy by integrating detailed military communications link models with existing military mission models.

Air Force hierarchy of models: a look inside the great pyramid

The widely-used Air Force hierarchy of models and simulations is generally depicted as a four-level pyramid; ranging from Engineering/Component Level up to Theater/Campaign Level. While it does present a concise picture of the scope of military models and simulations, it gives the impression that there is a smooth and natural transition from one level to the next. That is not the case. In fact, there is a great variance in degree of complexity from one level to the next. This paper looks at the state- of-practice in modeling and simulation in the context of this hierarchy; and in particular, at traditional and revolutionary techniques involving inter-level relationships.

A flexible simulation environment for command and control

A 1995 vision statement for Air Force Modeling and Simulation (M&S) highlighted the need for a Joint Synthetic Battlespace (JSB); an environment wherein warfighters could train and exercise on their real-world equipment while immersed in a realistic contingency or wartime environment. This paper describes our efforts to develop a Joint Synthetic Battlespace for Research and Development (JSB-RD), which will provide a realistic environment within which technologies being developed at AFRLs Information Directorate can be analyzed and tested. Where possible, this environment will attach to operational systems in order to provide military realism that will ultimately improve and shorten the tech transition process. This reconfigurable testbed will provide scalability and evolve over time building upon previous federations, attaching to other federations, while incorporating lessons learned along the way.

Joint synthetic battlespace for decision support (JSB-DS)

Joint Synthetic Battlespace for Decision Support (JSB-DS) is a developing set of concepts and an affiliated prototype environment with a goal of investigating the nature of decision support within a Command and Control (C2) context. To date, this investigation has focused on processing raw operational data into decision quality information and then presenting that information in a format that is useful and intuitive to a decision maker. The JSB-DS prototype was developed to support experimentation involving visual representation of, and interaction with, operational information. JSB-DSs prototype environment utilizes mission level battlefield simulations as a means to investigate decision and visualization aids with respect to situation awareness and reduction in decision timelines. These distributed simulations support dynamic re-tasking of Intelligence, Surveillance and Reconnaissance (ISR) and airborne strike assets within a Time Critical Target (TCT) prosecution vignette. The JSB-DS environment can serve as a basis for testing C2/TCT processes, procedures and training.

Using MRMAide for abstraction

Developing models for simulation is an arduous task. After building a high fidelity model, computation time can be prohibitive for general testing due to processing at higher levels of resolution. One way to address this problem is to develop abstract representations of the models that only consider “key” variables or parameters. For identifying these “key” variables or parameters, it may be desirable to determine the sensitivity of certain variables with respect to model outputs or response. One way of calculating the sensitivity of variables requires the analysis of output variables using clustering techniques. The MRMAide technology (MRMAide stands for Mixed Resolution Modeling Aide) employs a sensitivity analysis as an enabling technology that allows the program to test the sensitivity of certain variables and analyze the correlation of coupled variables. Using this tool helps the developer analyze how a model can be abstracted so that it can be rewritten to reduce the number of calculations but keeping an acceptable level of accuracy. Distributions can then be fed into these variables rather than calculating their values at each step resulting in a lower fidelity, yet fairly accurate representation for given operating conditions.

Model abstraction and the simulation sandbox

The Air Force Hierarchy of Models, often referred to as the Great Pyramid, depicts the four disparate levels of resolution in which models are typically categorized. These levels range from an Engineering/Component level at the bottom, to Theater/Campaign level at the apex of the pyramid. Today, the landscape of simulations has evolved from uni-purpose, stove-piped simulations to those that provide a Joint Vision encompassing a much broader scope. Within the simulation community, there exists the desire for model reuse, particularly when it involves the reuse of validated legacy codes. Much effort has been put forth to integrate existing models into a federated system. Integrating models of similar resolution is difficult enough; yet, even more difficult is the more prevalent situation where models are represented at different levels of resolution. Often referred to as Mixed Resolution Modeling (or Multiresolution Modeling), it is arguably the most pressing problem facing the simulation research community today. This paper will describe an attempt to address the MRM problem by applying model abstraction techniques to reduce the complexity of a detailed model without sacrificing the essence of the model. This surrogate version of the detailed model will then be able to play within a more aggregate simulation environment. To demonstrate, JSAF (Joint Semi- Automated Forces) will be used to simulate the behavior of models at both the detailed and abstract levels. The results will be compared to demonstrate the impact and utility of model abstraction.