METHODOLOGY Reusing a Simulation Facility Software Architecture for Embedded Simulation

On behalf of

Harmony An Architecture For Network Centric Heterogeneous Terrain Database Re-generation

Homogeneous proprietary online terrain databases are prolific. So also is the one directional generation and update process for these terrain databases. The existence of architectures and common ontologies that enable consistent and harmonious outcomes between distributed, multi-directional, heterogeneous terrain databases are lacking. Further due to technological change that empowers end-users, the expectations for immediate terrain database update are constantly increasing. As an example, a variety of incompatible synthetic environmental representations are used for military Modeling and Simulation applications. Regeneration and near-real-time update of compiled synthetic environments in a distributed, heterogeneous run time environment is an issue that is relevant to correlation of geospecific representations that are optimized for live, virtual, constructive and distributed simulation applications. Military systems of systems like the Future Combat Systems are emblematic of the regeneration challenge. The battlefields of the future will need constant updates of diverse synthetic representations of the real world environment. These updates will be driven by near real-time data from the battlefield as well as other constantly evolving intelligence and remote sensing sources. Since the Future Combat Systems will use embedded training, it will need to maintain a representation correlated with the actual battlefield as well as many other systems. To iv achieve this correlation, constant updates to the heterogeneous synthetic environment representations in the Future Combat Systems platforms will be required. An approach to overcoming the implicit bandwidth and communication limitations is to limit updates to changes only. Today’s traditional military Terrain Database (TDB) generation systems convert standard geographical source data products into many different target formats using what is refer to as pipeline flow paradigm. In the pipeline paradigm, TDBs are originally generated centrally upstream and flow downstream out to numerous divergent and distributed formats. In the pipeline paradigm, updates are centrally managed and distributed. This pipeline paradigm does not account for updates occurring on target formats and therefore such updates are not reflected upstream on the source data that originally generated the TDB. Since target format changes are not incorporated into the upstream geographical source data, adjacent streams of dependent target formats derived from the same geographical source data may not receive the changes either. The outcome of change in the pipeline TDB generation systems paradigm is correlation and interoperability errors between target formats as well as between the original upstream data source. An alternative paradigm that addresses data synchronization of geographical source data and target formats while accommodating bandwidth limitation is needed. This v dissertation proposes a “partial bi-directional TDB regeneration” paradigm, which envisions network based TDB updates between reliable partners. Partial bi-directional TDB regeneration is an approach that is very attractive as it reduces the amount of changes by only updating the affected target format data element. This research, presents an implementation of distributed, partial and bi-directional TDB regeneration through agent theory and ontologies over a network. Agent theory and ontologies are used to interpret data changes on external target formats and implement the necessary transformations on the Internal TDB generation system data elements to achieve consistency between all correlated representations. In this approach a variety of agents will exist and their behavior and knowledge will be customized based on ontologies that describe the target format. It is expected that such a system will provide a TDB generation paradigm that can address the implicit issues of: distribution, time, expertise, monetary, labor-constraints, and update frequency, while addressing the explicit issue of correlation between the external targets formats over time and at the same time reducing bandwidth requirements associated with traditional TDB generation system