Distributed Command and Control Systems with Intent-Based Networking: Effectiveness and Evaluation

With the dawn of the Information Age, modern systems are becoming increasingly complex across various domains, and emerging operational concepts require the integration of multiple complex systems into a system of systems (SoS). In the distributed Command-and Control (C2) domain, mission success depends on constructing adaptive mission chains (MCs) and mission paths (MPs) to enable decentralized C2 processes and achieve Commander’s Intent (CI). An MC is a set of tasks arranged temporally to achieve a given CI. An MP is an MC with SoS resources allocated to each task. The complex and rapidly shifting nature of the modern C2 space makes the creation of MPs and critical decision-making concerning those MPs increasingly multivariate and complex. While Intent-Based Networking (IBN) approaches can be employed to create multiple MPs, there is a need to evaluate multiple MPs over a multi-objective criterion to assess their utility and efficacy. This research focuses on Intent Achievement where MPs are evaluated based on CI. Specifically, this research investigates how Multi-Attribute Utility Theory (MAUT) using agility metrics can be applied to evaluate the effectiveness of feasible MPs in achieving a given CI. MAUT is a quantitative decision analysis technique employed to balance multiple competing objectives in decision making problems. The results demonstrate how a representative set of feasible MPs can be reduced to a single recommended MP that meets the given CI and how a sensitivity analysis can be performed to illuminate the trade-offs between objectives for the given set of MPs.