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

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

Madjid Tavana (Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA), Dawn A. Trevisani (Resilient Synchronized Systems Branch, Air Force Research Laboratory, Rome, NY, USA) and Jerry L. Dussault (Resilient Synchronized Systems Branch, Air Force Research Laboratory, Rome, NY, USA)
DOI: 10.4018/jitpm.2013040102
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Abstract

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.
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Introduction

Military organizations are composed of human operators interacting in structured relationships with technology towards the fulfillment of specific objectives. The increasing complexity and tight coupling between man and machines in military Command and Control (C2) systems has led to greater vulnerability due to system failure. Charles Perrow (1984) has described the function of any man-machine system along two clearly distinct dimensions of interaction and coupling.

Interaction refers to the number and nature of the connections between the components of a system. Linear interactions describe highly structured systems which are logical, sequential and planned. They function as a series of expected events in a predictable sequence. Flaws in one component can be identified and corrected with little disturbance to the overall system. On the other hand, flaws in complex interactions are not visible, and often cannot be comprehended as they unfold. Complex interactions involving unfamiliar, unplanned, unexpected and unforeseeable sequences influence the system’s robustness (the ability to avoid failure).

Coupling refers to how quickly and explosively a change in one component of an organization is felt in another. The components of a system are coupled (or joined together) loosely when they are not very dependent on each other. The components are coupled tightly when the parts are highly interdependent. In tightly coupled systems a change in one component rapidly affects the status of other components and influences the system’s resiliency (or ability to recover).

The interaction and coupling, whether by design or inadvertently, determine the system’s susceptibility to vulnerabilities and make failures not only inevitable but normal. A system accident can be very easy to see in hindsight, but very difficult to see in foresight. Ahead of time, there are simply too many possible action pathways to seriously consider all of them. Therefore, C2 systems are subject to higher failure rates because the complex interactions among their components cannot be thoroughly planned, understood, anticipated and guarded against. In addition, the C2 systems coordinate execution of logically related tasks. Since vulnerabilities cannot be completely eliminated in a C2 system and preventive measures sometimes fail, the C2 system may be subject to intentional malicious attacks. A malicious attacker may create a prohibited task or corrupt an existing task in the C2 systems. This malicious act may trigger some other tasks in the system due to the existence of complex interactions.

Robustness, a proactive concept, is the ability of the system to avoid failure, and resiliency, a reactive concept, is the ability of the system to recover from failure once it occurs. Although the ability to avoid and recover from failure is important in many complex systems, the idea of self-protecting and self-healing systems is frequently discussed independently in the literature (Dragoni et al., 2009). We argue that typical precautions focusing on robustness or resiliency is inadequate and may help create new categories of failures in complex systems. In this paper, we consider both the proactive and reactive concepts and propose an interactive framework for simultaneous consideration of robustness and resiliency in military C2 Systems. The proposed 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. Robustness and resiliency are measured with multiple criteria (i.e. repair-recovery costs and repair-recovery completion times). 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 of the C2 system.

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