On simulation model complexity
Proceedings of the 32nd conference on Winter simulation
IEEE Transactions on Software Engineering
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Capability-based acquisition changes the general approach to systems engineering. Instead of buying threat-based, service-specific systems, a mobile target-weapon pairing system, for example, and then identifying how to integrate that system with other similar threat-based systems, we now identify the warfighting capabilities we want to achieve. Then we start with a 'blank sheet of paper' to develop the systems architecture and technical standards necessary to allow seamless interaction using shared data and applications. [1] Capability-based acquisition focuses on the development of alternative system of systems (SoS) architectures that link (i.e., network) diverse interoperable systems to optimize overarching capability effectiveness while minimizing development costs. It is up to the systems architect and engineer to find the best solution by examining inter-relationships between various configurations of warfighters, platforms, sensors, weapons, command and control, communications, while considering external factors that potentially impact full capability effectiveness and sustainment, such as operational doctrine, joint operations, government and societal organizations, terrorism, and public opinion. The emergence of asymmetric warfare, military-operations-other-than-war, effects-based and network-centric operations, national crisis response (and other homeland security missions), and other large scale problems where many diverse systems (often human individual and organizational decision-making systems) interact in complex ways, serves to complicate the process of developing an effectively interoperable system. It is a complex undertaking to integrate a complex system of systems. Accordingly, the concept of system of systems has become increasingly important to systems engineering. One needs to understand the nature of the complexity of system of systems to gain insight into the design of robust, interoperable systems that integrate seamlessly into a system of systems environment. Complexity - regardless of whether a system is hardware, software, or people - is generally a function of the number of entities (nodes) in the system, the number of relations (interfaces, interactions, networks), and time dependence (of interactions). Added complexity emerges when systems are capable of adapting their behavior to meet changing environmental conditions (complex adaptive systems) and when systems are capable of learning or evolving new behaviors. This paper explores a set of metrics that define the complexity of a system of systems simulation and presents preliminary work underway to apply these ideas for improving the quality and efficiency of the systems engineering process.