We propose FAUST, the Finite-field Algebra for Unbeatable Situational-awareness in Tactical-networks. FAUST utilizes Boston Universitys CPISync, an advanced data set reconciliation primitive that significantly improves synchronization and transmission of different types of Situational Awareness information among nodes using common SA platforms. FAUST offers better performance for dissemination of information vs. commonly used approaches of flooding or epidemic dissemination. Information types that can be reconciled encompass SA, data and geographical, and network topology. CPISync supports scalable dissemination, providing information-theoretic guarantees on communication complexity. It is a lower level protocol that maximizes the value of the information exchanged during an encounter (data synchronization). This primitive improves network performance by enabling larger aggregation of data (scalability), higher data collection rates during link failures, and efficient utilization of low bandwidth data links. These protocols tie together with network-wide protocols that work when no end-to-end paths are available and that provide persistence to data (survivability). In Phase I, SSCI will demonstrate performance improvement over baseline standard data synchronization mechanisms for ordered data, using a virtual network. Comparison metrics include communication latency, energy consumption, and volume of data synchronized per unit time. Phase II will enable user self-management in the field, such as allowing the users to select the groups that it belongs to.
Keywords: Data Reconciliation, Data Synchronization, Data Set Reconciliation, Force Xxi Battle Command Brigade And Below (Fbcb2), Situational Awareness (Sa), Tactical Networks, Store-Ca