Performance modeling of the advanced field artillery tactical data system

Planning of complex activities is a deliberative process and automation support for re-planning activities should provide for cognitive modeling of the planning process. One approach for modeling military planning systems is to partition the process into separable components and analyze the components individually. This paper takes the position that the cognitive model should contain details of the domain being supported and, especially for support of on-line re-planning, knowledge of the system implementation architecture – including performance modeling of the implementation architecture. A possible issue is the failure of the separable components assumption when the system is composed of components (i.e. components are not separable when the inputs to system components are affected by the outputs of the components). We discuss these thoughts in some detail and provide an overview of a test bed framework being implemented to perform experiments on the validity of this approach. In particular, we are interested in creating analysis tools that apply metrics to sensed data to assist in determining when a re-planning activity is required and in prioritizing re-planning activities. The framework is intended to support experiments with military decision making and, in particular, with re-planning activities that support execution of a military Operation Order (OPORD). We are investigating use of a new simulation tool to accumulate information at the message-packet-level and perform analysis at the network-application-level. We discuss use of this framework for pattern recognition of activities distributed in time and space. We provide an introduction to our approach for partitioning the problem space and some ideas on design of experiments using this approach. Finally, we assert that this level of detail is required to enable assessment of the information assurance situation to support evaluation of risks, as well as implementation and application of metrics for analysis of alternatives for reacting to attacks and monitoring of the selected alternatives.