Scalable Adaptive Architectures for Maritime Operations Center Command and Control

Abstract : The overall objective of the effort was to study and analyze the new concepts of the Navy Maritime Operations Center (MOC) focusing on the scalability aspects of the MOC concept and develop tools and techniques that could support the design and evaluation of augmentation strategies that will allow MOCs to change or adapt to new missions and new levels of command and control. Specifically, the effort focused on developing an understanding of the issues involved in determining the fundamental principles ad factors involved in changing the scale of a MOC through augmentation including information needed to design and analyze how to change a MOC's organization structures and underlying architecture as its mission changes. We accomplished both objectives through a set of six tasks. A suite of tools was upgraded and modified that can support the modeling and analysis of MOC scalability. Several workflows were developed that support the process of using the tools to enable the design of MOC augmentation strategies. Techniques for considering the impact of cyber contested environments and space limitations on command vessels were developed. The tools were integrated into a test bed called the C2 Wind Tunnel. Scenarios were created and evaluated using the tools to demonstrate the tools and workflows. A task was added later in the project to investigate the possibility of using earlier work on the validation and verification of rule bases in addressing the dynamically changing rules of engagement of a maritime force as it crosses different geographical areas. GMU developed an approach that uses a formal model checking methodology to detect redundant and inconsistent cases in a set of rules selected from across different Maritime Laws. The approach can provide considerable help to a Maritime Lawyer, i.e., a Staff Judge Advocate (SJA) in deciding the set of legal actions from the applicable rules after careful consideration of the cases identified by it.