WSC 2007 Final Abstracts

Military Applications Track

Monday 10:30:00 AM 12:00:00 PM
Military Keynote

Chair: J.A. Hamilton, Jr. (Auburn University)

Military Keynote Address
John C. Deal (BAE Systems Inc.)

Military keynote address delivered by John C. Deal, Vice President of the Systems Engineering Electronics and Integrated Solutions Operating Group at BAE Systems Inc.

Monday 1:30:00 PM 3:00:00 PM
UAV Simulation

Chair: Yan Gu (Georgia Institute of Technology)

Validating a Network Simulation Testbed for Army UAVs
Stephen Samuel Hamilton and Timothy Schmoyer (United States Military Academy) and John Hamilton (Auburn University)

Auburn University, through the Army's Aviation and Missile Research, Development and Engineering Center (AMRDEC) has been supporting the Unmanned Systems Initiative (USI) program in three research areas related to unmanned aerial vehicle (UAV). A major element in this work is the development of a high fidelity modeling and simulation testbed to support the USI program. This paper describes the testbed and the verification and validation of the testbed.

Simulation-aided Path Planning of UAV
Farzad Kamrani and Rassul Ayani (Royal Institute of Technology (KTH))

The problem of path planning for Unmanned Aerial Vehicles (UAV) with a tracking mission, when some a priori information about the targets and the environment is available can in some cases be addressed using simulation. Sequential Monte Carlo Simulation can be used to assess the state of the system and target when the UAV reaches the area of responsibility and during the tracking task. This assessment of the future is then used to compare the impact of choosing different alternative paths on the expected value of the detection time. A path with a lower expected value of detection time is preferred. In this paper the details of this method is described. Simulations are performed by a special purpose simulation tool to show the feasibility of this method and compare it with an exhaustive search.

Self Organized UAV Swarm Planning Optimization for Search and Destroy Using SWARMFARE Simulation
Dustin J. Nowak (Air Force Institute of Technology), Ian Price (AEDC) and Gary B. Lamont (Air Force Institute of Technology)

As military interest continues to grow for Unmanned Aerial Vehicle (UAV) capabilities, the Air Force is exploring UAV autonomous control, mission planning and optimization techniques. The SWARMFARE simulation system allows for Evolutionary Algorithm computations of swarm based UAV Self Organization (SO). Through Swarmfare, the capability exists to evaluate guiding behaviors that allow autonomous control via independent agent interaction with its environment. Current results show that through an implementation of ten basic rules the swarm forms and moves about a space with reasonable success. The next step is to focus on optimization of the formation, traversal of the search space and attack. In this paper we cover the capabilities, initial research results, and way ahead for this simulation. Overall the SWARMFARE tool has established a sandbox in which it is possible to optimize these and build new behaviors.

Monday 3:30:00 PM 5:00:00 PM
Military Communications

Chair: Susan Heath (Naval Postgraduate School)

Simulation of Army Unmanned Aerial Vehicle Communications
Richard Chapman, Drew Hamilton, Daniel Box, Stephen Hamilton, Mark Kuhr, and Jonathan MacDonald (Auburn University)

We explore development of a high-fidelity simulation testbed for various network architectures for communication between components of tactical unmanned aerial systems, and for distribution of intelligence gathered by these systems.

Applying Parallel and Distributed Simulation to Remote Network Emulation
Yan Gu and Richard Fujimoto (Georgia Institute of Technology)

Many of today's military services and applications run on geographically distributed sites and need to be tested and evaluated under realistic scenarios with many unpredictable factors. A remote network emulation framework called ROSENET is proposed that can meet this requirement by using a remote parallel simulation server to model the wide area network and a local network emulator to provide timely QoS predictions for real world applications. This paper discusses problems faced in applying parallel and distributed simulation technique for the remote network emulation. The experimental results show that timeliness and remote accessibility are main concerns in applying parallel simulation to remote network emulation.

Application of BML to Inter-agent Communication in the ITSimBw Simulation Environment
Philipp Huegelmeyer (Bundesamt fur Sicherheit in der Informationstechnik), Ulrich Schade (FGAN) and Thomas Zoeller (Fraunhofer IAIS)

In this contribution we analyze communication requirements of multi-agent simulation systems using ITSimBw - developed at Fraunhofer IAIS - as an example. A focus is put on issues concerning inter-agent communication but complementary aspects of user interaction and coupling with C2 systems are also discussed. We propose an augmented version of the battle management language BML as a communication protocol that perfectly matches our communication requirements both syntactically as well as on the semantic level. We furthermore explain how such BML messages are processed by our system.

Tuesday 8:30:00 AM 10:00:00 AM
Military Modeling

Chair: Arnold Buss (Naval Postgraduate School)

Using a Low-resolution Entity Model for Shaping Initial Conditions for High-resolution Combat Models
Darryl Ahner (U.S. Army TRADOC Analysis Center-Monterey), Arnold H. Buss (Naval Postgraduate School) and John Ruck (Rolands and Associates)

Determining the initial conditions for high-resolution combat models presents a challenging modeling problem. These initial conditions can have a major impact on the outcome of the analysis, and yet there is a significant difficulty setting those conditions in a manner that spans the important areas of the input factor space. This paper presents a method for setting those initial conditions using a low-resolution, entity-level combat model, Joint Dynamic Allocation of Fires and Sensors (JDAFS). Like its predecessor DAFS, JDAFS models entities on the battlefield, but to a lower degree of detail than most high-resolution combat models. This allows substantial exploration of the input factor space, and can help make the eventual high-resolution simulation runs more effective.

Model-based Measurement of Situation Awareness
W. Scott Neal Reilly and Sean L. Guarino (Charles River Analytics, Inc.) and Bret Kellihan (DCS Corporation)

Decision making in complex environments in the face of uncertain and missing information is a daunting task. We describe a modeling and simulation based approach to providing planners, analysts, and decision makers with a better understanding of the effect of imperfect information on the reliability of decisions made in such situations. We use techniques adopted from Sensitivity Analysis to evaluate the sensitivity of particular decision-making procedures to the uncertainty associated with the information that is being used to make the decision. We use this analysis to support the development of more robust decision-making procedures and effective and efficient information-gathering plans. We demonstrate how these tools can be used in both on-line decision analysis and off-line decision evaluation and development, and we describe how these tools can be used to support complex simulation systems such as the U.S. Army's Modeling Architecture for Technology and Research EXperimentation (MATREX).

A Simulation Model for Military Deployment
Ugur Ziya Yıldırım, Ihsan Sabuncuoglu, and Barbaros Tansel (Bilkent University)

The Deployment Planning Problem (DPP) for military units may in general be defined as the problem of planning the movement of geographically dispersed military units from their home bases to their final destinations using different transportation assets and a multimodal transportation network while obeying the constraints of a time-phased force deployment data describing the movement requirements for troops and equipment. Our main contribution is to develop a GIS-based, object-oriented, loosely-coupled, modular, platform-independent, multi-modal and medium-resolution discrete event simulation model to test the feasibility of deployment scenarios. While our simulation model is not a panacea for all, it allows creation and testing the feasibility of a given scenario under stochastic conditions and can provide insights into potential outcomes in a matter of a few hours.

Tuesday 10:30:00 AM 12:00:00 PM
Operational Use of Military Simulation

Chair: Alan Johnson (Air Force Institute of Technology)

Analyzing Air Combat Simulation Results with Dynamic Bayesian Networks
Jirka Lauri Poropudas and Kai Matti Virtanen (Helsinki University of Technology)

In this paper, air combat simulation data is reconstructed into a dynamic Bayesian network. It gives a compact probabilistic model that describes the progress of air combat and allows efficient computing for study of different courses of the combat. This capability is used in what-if type analysis that investigates the effect of different air combat situations on the air combat evolution and outcome. The utilization of the dynamic Bayesian network is illustrated by analyzing simulation results produced with a discrete event air combat simulation model called X-Brawler.

Integration of Underwater Sonar Simulation with a Geographical Information System
Yanshen Zhu, Serge Sala-Diakanda, Luis Rabelo, Jose A. Sepulveda, and Maria Teresa Bull (University of Central Florida)

This paper discusses the integration of a geographical information system (GIS) with a simulation model of the sensors (active and passive) used as components of a detection system on US Navy ships. The simulation model is a tool developed to improve threat recognition, undersea tactical awareness, countermeasure emissions, and counter-weapon fire control that enables surface ships to survive a salvo of torpedo attacks. The model, was implemented (2005-2006) in Java using AnyLogic?(by XJ Technologies). A commercial GIS application provides data visualization, query, analysis, and integration capabilities along with the ability to create and edit geographic data. The simulation model runs and seamlessly gets geographical information from ArcGIS (by ESRI corporation) in order to make decisions such as avoiding a ship going aground. Statistics and animations are controlled by the simulation software, while the maps and the movements of the environment object above of the map is handled by ArcGIS.

Using Discrete Event Simulation to Examine Marine Training at the Marine Corps Communication-Electronics School
Jon W. Davenport, Charles R. Neu, William R. Smith, and Susan K. Heath (Naval Post Graduate School)

This paper presents a discrete-event simulation model used to explore various possibilities for improving the training continuum at the Marine Corps Communication-Electronics School. The goal of the analysis is to reduce the average waiting time experienced by Marines as they wait for their formal training to commence. Results show that the implementation of even the least beneficial of these improvements yields a 37 percent reduction in waiting time. The best single change yields an 82 percent reduction. This translates into a 30 day reduction in average waiting time per Marine. If all improvements were implemented, a reduction of 88 percent could be achieved, bringing the average waiting time per Marine down to less than 5 days.

Tuesday 1:30:00 PM 3:00:00 PM
Advanced Techniques in Military Simulation

Chair: Robert Owor (Albany State University)

A Knowledge-based Method for the Validation of Military Simulation
Feiyan Min, Ping Ma, and Ming Yang (Harbin Institute of Technology)

The validation of modern military simulation relies heavily on the opinions of military experts, and it makes the validation task exhaustive and time-consuming. The knowl-edge-based methods can be applied for these problems. There are three kinds of knowledge sets in military simulation validation, namely, domain knowledge, inference knowledge and validation task knowledge. By analyzing the context of these knowledge, three types of knowledge models are developed. Based on these knowledge models, the implement of knowledge-based system is detailed. However, this validation system can be practical for the validation of military simulation by enriching the knowledge base.

Blending Systems Engineering Principles and Simulation-based Design Techniques to Facilitate Military Prototype Development
Stephanie J. Lackey and Johathan T. Harris (Naval Air Warfare Center Training Systems Division) and Linda C. Malone and Denise M. Nicholson (University of Central Florida)

Tactical communications represent a critical skill set to military training at the individual service level and to the joint military community. As the complexity of the operational environment increases, the methods and devices employed to address tactical communications training follow suit. One mitigation approach incorporates simulation tools by merging live training elements with virtual, or simulated, training devices. Thus, integrating live and virtual components is particularly important to the tactical communications training domain. A logical step in the advancement of live-to-virtual communications is the development of a device capable of merging, managing, and allocating multiple requests for live radio resources in a dynamic live, virtual, constructive configuration. This paper details the application of systems engineering principles and simulation-based design to the development of a prototype Integrated Live-to-Virtual Communications Server. A detailed discussion of the developmental approach and its impact upon cost, schedule, and technical risks is provided.

Feasibility Study of Variance Reduction in the Logistics Composite Model
George P. Cole III, Alan W. Johnson, and John O. Miller (Air Force Institute of Technology)

The Logistics Composite Model (LCOM) is a stochastic, discrete-event simulation that relies on probabilities and random number generators to model scenarios in a maintenance unit and estimate optimal manpower levels through an iterative process. Models such as LCOM involving pseudo-random numbers inevitably have a variance associated with the output of the model for each run. Reducing this output variance can be costly in the additional time needed for multiple replications. This research explores the application of three different methods for reducing the variance of the model's output. The methods include Common Random Numbers, Control Variates, and Antithetic Variates. The result is a successful variance reduction in the primary output statistics of interest using the application of the Control Variates technique, as well as a methodology for the implementation of Control Variates in LCOM.

Tuesday 3:30:00 PM 5:00:00 PM
Security in Military Simulation

Chair: Stephen Hamilton (United States Military Academy)

A Simulation Framework for Energy-efficient Data Grids
Ziliang Zong, Kiranmai Bellam, and Xiao Qin (Auburn University) and Yiming Yang (Intel Corporation)

High performance data grids increasingly become popular platforms to support data-intensive applications. Reducing high energy consumption caused by data grids is a challenging issue. Most previous studies in grid computing focused on performance and reliability without taking energy conservation into account. As such, designing energy-efficient data grids system becomes highly desirable. In this paper, we propose a framework to simulation energy-efficient data grids. We present an approach to integrating energy-aware allocation strategies into energy-efficient data grids. Our framework aims at simulating a data grid that can conserve energy for data-intensive applications running on data grids.

An Elliptical Curve Cryptographic Algorithm for Wireless RF Systems
Robert Steven Owor, Khalil Dajani, and Zephyrinus Okonkwo (Albany State University) and John Hamilton (Auburn University)

In this paper, we propose a new asymmetric cryptographic algorithm (HOOD CRYPT) based on the Elliptical Curve Cryptographic approach. The algorithm describes how an orthogonal frequency division multiplexing (OFDM) based RF wireless system can be encrypted using planner matrix Elliptical Curve Cryptography (ECC). The newly described asymmetric algorithm can be applied to the OFDM transmission scheme in the design of more robust and secure cryptography in portable wireless devices. An analysis of the proposed algorithm is made using the discrete logarithm approach. Two methods, namely, Pollard's rho Attack and Index Calculus are investigated with respect to the new algorithm. We found that our method makes it even more difficult to break the ECC encryption.

Real-time Prediction in a Stochastic Domain Via Similarity-based Data-mining
Timo Steffens and Philipp Huegelmeyer (Fraunhofer IAIS)

This paper introduces an application and a methodology to predict future states of a process under real-time requirements. The real-time functionality is achieved by creating a Bayesian tree via data-mining on agent-based simulations. The computationally expensive parts are handled in an offline phase, while the online phase is computationally cheap. In the offline phase the simulations are run and meaningful clusters of states are identified by use of virtual attributes. Then the transition probabilities between states of different clusters are organized in a Bayesian tree. Finally, in the online phase similarity measures are used again in order to classify query states into the clusters and to infer the probability of future states. The application domain is the support of military units during missions and maneuvers.

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