Throughout the Department of Defense (DoD), acquisition, platform integration, and life cycle costs for weapons systems have continued to rise. Although Open Architecture (OA) interface standards are one of the primary methods being used to reduce these costs, the Air Force Rapid Capabilities Office (AFRCO) has extended the OA concept and chartered the Open Mission System (OMS) initiative with industry to develop and demonstrate a consensus-based, non-proprietary, OA standard for integrating subsystems and services into airborne platforms. The new OMS standard provides the capability to decouple vendor-specific sensors, payloads, and service implementations from platform-specific architectures and is still in the early stages of maturation and demonstration. The Air Force Research Laboratory (AFRL) - Sensors Directorate has developed the Blue Guardian program to demonstrate advanced sensing technology utilizing open architectures in operationally relevant environments. Over the past year, Blue Guardian has developed a platform architecture using the Air Force's OMS reference architecture and conducted a ground and flight test program of multiple payload combinations. Systems tested included a vendor-unique variety of Full Motion Video (FMV) systems, a Wide Area Motion Imagery (WAMI) system, a multi-mode radar system, processing and database functions, multiple decompression algorithms, multiple communications systems, and a suite of software tools. Initial results of the Blue Guardian program show the promise of OA to DoD acquisitions, especially for Intelligence, Surveillance and Reconnaissance (ISR) payload applications. Specifically, the OMS reference architecture was extremely useful in reducing the cost and time required for integrating new systems.
KEYWORDS: Process modeling, Lawrencium, Process control, Data modeling, Computer simulations, C4ISR, Control systems, Modeling and simulation, Computer architecture, Systems modeling
The Virtual Testbed for Advanced Command and Control Concepts (VTAC) program is performing research and development efforts leading to the creation of a testbed for new Command and Control (C2) processes, subprocesses and embedded automated systems and subsystems. This testbed will initially support the capture and modeling of existing C2 processes/subprocesses. Having modeled these at proper levels of abstraction, proposed revisions or replacements to processes, systems and subsystems can be evaluated within a virtual workspace that integrates human operators and automated systems in the context of a larger C2 process. By utilizing such a testbed early in the development cycle, expected improvements resulting from specific revisions or replacements can be quantitatively established. Crossover effects resulting from changes to one or more interrelated processes can also be measured. Quantified measures of improvement can then be provided to decision makers for use in cost-to-performance benefits analysis prior to implementing proposed revisions, replacements, or a sequence of planned enhancements.
This paper first presents a high-level view of the VTAC project, followed by a discussion of an example C2 process that was captured, abstracted, and modeled. The abstraction approach, model implementation, and simulations results are covered in detail.
KEYWORDS: Local area networks, Performance modeling, Modeling and simulation, Internet, Data fusion, Computer simulations, Data communications, Data mining, Systems modeling, Process modeling
The Joint Battlespace Infosphere (JBI) program is performing a technology investigation into global communications, data mining and warehousing, and data fusion technologies by focusing on techniques and methodologies that support twenty first century military distributed collaboration. Advancement of these technologies is vitally important if military decision makers are to have the right data, in the right format, at the right time and place to support making the right decisions within available timelines. A quantitative understanding of individual and combinational effects arising from the application of technologies within a framework is presently far too complex to evaluate at more than a cursory depth. In order to facilitate quantitative analysis under these circumstances, the Distributed Information Enterprise Modeling and Simulation (DIEMS) team was formed to apply modeling and simulation (M&S) techniques to help in addressing JBI analysis challenges. The DIEMS team has been tasked utilizing collaborative distributed M&S architectures to quantitatively evaluate JBI technologies and tradeoffs. This paper first presents a high level view of the DIEMS project. Once this approach has been established, a more concentrated view of the detailed communications simulation techniques used in generating the underlying support data sets is presented.
State-of-the-art simulation computing requirements are continually approaching and then exceeding the performance capabilities of existing computers. This trend remains true even with huge yearly gains in processing power and general computing capabilities; simulation scope and fidelity often increases as well. Accordingly, simulation studies often expend days or weeks executing a single test case. Compounding the problem, stochastic models often require execution of each test case with multiple random number seeds to provide valid results. Many techniques have been developed to improve the performance of simulations without sacrificing model fidelity: optimistic simulation, distributed simulation, parallel multi-processing, and the use of supercomputers such as Beowulf clusters. An approach and prototype toolset has been developed that augments existing optimization techniques to improve multiple-execution timelines. This approach, similar in concept to the SETI @ home experiment, makes maximum use of unused licenses and computers, which can be geographically distributed. Using a publish/subscribe architecture, simulation executions are dispatched to distributed machines for execution. Simulation results are then processed, collated, and transferred to a single site for analysis.
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