: Non-combatants have become an important aspect of U.S. military operations in urban areas. Recent experience shows how non-combatants can affect the United States ability to meet tactical and strategic objectives in engagements across the spectrum of warfare. However, there is currently little systematic research on civilian behavior within the defense community, including the military modeling community. As the policy questions about dealing with civilians continue to gain in importance, further research on noncombatants would be beneficial. This dissertation reviews recent urban operation campaigns and attempts to provide background research that will assist in incorporating non-combatants into models, simulations, training scenarios, and other analytic tools in a more formal way. It identifies noncombatant behavior from recent urban operations that have affected U.S. military activities. It recommends a layered approach to civilian behavior, beginning with basic population density and other demographic characteristics. To this, it adds simple and then complex behaviors.

/pdf/ignoring-the-innocent-non-combatants-in-urban-operations-and-1yy2usc54m.pdf

Ignoring the Innocent: Non-combatants in Urban Operations and in Military Models and Simulations

A software framework is an architecture or infrastructure intended to enable the integration and interoperation of software components. Specialized types of software frameworks are those specifically intended to support the composition of models or other components within a simulation system. Such frameworks are intended to simplify the process of assembling a complex model or simulation system from simpler component models as well as to promote the reuse of the component models. Several different types of software frameworks for model composition have been designed and implemented; those types include common library, product line architecture, interoperability protocol, object model, formal, and integrative environment. The various framework types have different components, processes for composing models, and intended applications. In this survey the fundamental terms and concepts of software frameworks for model composition are presented, the different types of such frameworks are explained and compared, and important examples of each type are described.

/pdf/software-frameworks-for-model-composition-3jerl7ef1v.pdf

Software frameworks for model composition

Urban operations currently are of great concern to the defense community. J9, the Experimentation Directorate of USJFCOM, and the Joint Advanced Warfighting Program currently are conducting an experiment to investigate concepts for applying future technologies to joint urban operations. The first phase of the experiment focused on employing future sensors to remotely monitor and understand enemy operations in a foreign city. Characteristics of the urban environment include high building density, a large civilian population, and a cultural environment. These characteristics pose significant challenges for simulation designers. This paper describes the modifications required to adapt the simulations supporting the experiment, JSAF and SLAMEM, to the urban environment. A landscape with a large number of buildings had to be automatically generated and represented in a space efficient manner. Large concentrations of vehicles and pedestrians had to be modeled moving realistically through the city. This behavior...

/pdf/adapting-to-urban-warfare-q3w8j29adv.pdf

Adapting to Urban Warfare

This paper describes several challenges facing programmers of future edge computing systems, the diverse many-core devices that will soon exemplify commodity mainstream systems. To call attention to programming challenges ahead, this paper focuses on the most complex of such architectures: integrated, power-conserving systems, inherently parallel and heterogeneous, with distributed address spaces. When programming such complex systems, new concerns arise: computation partitioning across functional units, data movement and synchronization, managing a diversity of programming models for different devices, and reusing existing legacy and library software. We observe that many of these challenges are also faced in programming applications for large-scale heterogeneous distributed computing environments, and current solutions as well as future research directions in distributed computing can be adapted to commodity computing environments. Optimization decisions are inherently complex due to large search spaces of possible solutions and the difficulty of predicting performance on increasingly complex architectures. Cognitive techniques are well suited for managing systems of such complexity, citing recent trends of using cognitive techniques for code mapping and optimization support. Combining these, we describe a fundamentally new programming paradigm for complex heterogeneous systems, where programmers design self-configuring applications and the system automates optimization decisions and manages the allocation of heterogeneous resources.

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

This paper describes several challenges facing programmers of future edge computing systems, the diverse many-core devices that will soon exemplify commodity mainstream systems. To call attention to programming challenges ahead, this paper focuses on the most complex of such architectures: integrated, power-conserving systems, inherently parallel and heterogeneous, with distributed address spaces. When programming such complex systems, new concerns arise: computation partitioning across func- tional units, data movement and synchronization, managing a diversity of programming models for different devices, and reusing existing legacy and library software. We observe that many of these challenges are also faced in programming applications for large-scale heterogeneous distributed com- puting environments, and current solutions as well as future research directions in distributed computing can be adapted to commodity computing environments. Optimization deci- sions are inherently complex due to large search spaces of possible solutions and the difficulty of predicting perfor- mance on increasingly complex architectures. Cognitive techniques are well suited for managing systems of such complexity, citing recent trends of using cognitive techniques for code mapping and optimization support. Combining these, we describe a fundamentally new programming paradigm for complex heterogeneous systems, where programmers design self-configuring applications and the system automates optimization decisions and manages the allocation of hetero- geneous resources.

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques Applying a wider range of machine-learning techniques to an increased number of programming decisions may produce more effective systems for new-generation computers.

The U. S. Joint Forces Command (JFCOM) has the requirement to conduct joint experimentation for the Department of Defense (DoD). The JFCOM staff agency responsible to lead joint experiments is the J9. Joint experimentation is used to develop transformational warfighting concepts, technology, and processes through a series of wargaming and simulation activities, typically culminating with a large human-in-the-loop event. Thus far these events have been independent, each with its own setup, integration, execution, and teardown. To accelerate experimentation, include the Services and Allies, and reduce per event costs, J9 is transforming the way it executes experiments by creating the Distributed Continuous Experimentation Environment (DCEE). Initially, the DCEE will simply reduce overhead by creating a standing simulation infrastructure, including the Joint Experimental Federation (JEF) built for Millennium Challenge 2002 (MC02) and Service facilities. The DCEE will be a continuously evolving capability incorporating the latest simulation developments from the Services and other sources. DCEE expansion will be accomplished by linking additional simulations into the JEF, embedding new models in the existing federates, and linking with other federations. Preliminary DCEE development efforts have included: integrating scaleable computing power via the inclusion of DoD High Performance Computing assets; the development of a worldwide terrain database with high resolution inserts, including urban environments; developing a real time data collection and analysis capability; and developing simulation monitoring and control functions. A network of J9 and Service sites is being established to provide USJFCOM with a highly flexible, evolving, and distributed experimentation capability based on interlinked federations of simulations.

/pdf/moving-toward-a-distributed-continuous-experimentation-51ezg6cm41.pdf

Moving toward a Distributed Continuous Experimentation Environment

Within the Department of Defense, multiple architectures are created to serve and fulfill one or several specific service or mission related LVC training goals. Multiple Object Models exist across and within those architectures and it is there that those disparate object models are a major source of interoperability problems when developing and constructing the training scenarios. The two most commonly used architectures are; HLA and TENA, with DIS and CTIA following close behind in terms of the number of users. Although these multiple architectures can share and exchange data the underlying meta-models for runtime data exchange are quite different, requiring gateways/translators to bridge between the different object model representations; while the Department of Defense's use of gateways are generally effective in performing these functions, as the LVC environment increases so too does the cost and complexity of these gateways. Coupled with the wide range of different object models across the various user communities we increase the propensity for run time errors, increased programmer stop gap measures during coordinated exercises, or failure of the system as a whole due to unknown or unforeseen incompatibilities. The Joint Composable Object Model (JCOM) project was established under an MS the Conceptual Model Development Format, the Common Object Model, the Architecture Neutral Data Exchange Model (ANDEM), and the association methodology to allow the re-use of multiple architecture object models and the development of the prototype persistent reusable library.

/pdf/joint-composable-object-model-and-lvc-methodology-3p7nidojk0.pdf

Joint Composable Object Model and LVC Methodology

A proposal for a data exchange model representation standard

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Adapting to Urban Warfare

Moving toward a Distributed Continuous Experimentation Environment

Joint Composable Object Model and LVC Methodology

A proposal for a data exchange model representation standard