Information Flow: Tactical Network Design and Bandwidth Management University XXI Texas A&M University University of Texas United States Army.

Slides:



Advertisements
Similar presentations
Live, Virtual, Constructive – Integrating Architecture
Advertisements

Third Generation Adaptive Hypermedia Systems Curtis A. Carver Jr., John M.D. Hill and Udo W. Pooch.
ARCH-05 Application Prophecy UML 101 Peter Varhol Principal Product Manager.
Chapter 19: Network Management Business Data Communications, 5e.
Tactical Event Resolution Using Software Agents, Crisp Rules, and a Genetic Algorithm John M. D. Hill, Michael S. Miller, John Yen, and Udo W. Pooch Department.
Collaboration Proposal Proposed Interaction between CSDL and AAI With Narration by Nicholas J. Parks.
Force XXI Battle Command Brigade and Below (FBCB2) Communications System
Anticipatory Planning Support System John M. D. Hill Lieutenant Colonel, U. S. Army Assistant Professor, USMA Ph.D. Candidate, TAMU Dr. Udo W. Pooch Department.
United States Marine Corps
Distribution A: Approved for public release; distribution is unlimited Get the right M&S technology to the right place, at the right time, for the Decision.
Intelligent Network Configuration Optimization Toolkit (INCOT) Robert Richards, Ph.D. Coskun Tasoluk Stottler Henke Associates, Inc. San Mateo, CA
Chapter 19: Network Management Business Data Communications, 4e.
Common Operational Picture
Common Operational Picture
United States Army Combined Arms Center TIER III SUPPORT.
1 Chapter 12: Decision-Support Systems for Supply Chain Management CASE: Supply Chain Management Smooths Production Flow Prepared by Hoon Lee Date on 14.
TEXAS A&M UNIVERSITY AND THE UNIVERSITY OF TEXAS AT AUSTIN Army Digitization Research Initiative Dr. Richard A. Volz (Computer Science) Dr. Tom Ioerger.
1 ITC242 – Introduction to Data Communications Week 12 Topic 18 Chapter 19 Network Management.
Title put our names here. General Problem Statement Ability to give customized information to a user based on the user’s current location, the current.
C 4 I for the Objective Force 2800 Powder Mill Rd Adelphi, MD Direct Fire Function Infantry Carrier Function Indirect.
Managing Agent Platforms with the Simple Network Management Protocol Brian Remick Thesis Defense June 26, 2015.
1 By Vanessa Newey. 2 Introduction Background Scalability in Distributed Simulation Traditional Aggregation Techniques Problems with Traditional Methods.
Chapter 8 Management Support and Coordination Systems.
Program Analysis & Evaluation 1 © 2006 July 13, /18/98 2:13 PM Research Sponsors Robert Flowe, Gary Bliss OSD Program Analysis and Evaluation, Resource.
KM enhances mission command, facilitates the exchange of knowledge, supports doctrine development, fosters leaders’ development, supports lessons learned,
Defence R&D Canada R et D pour la défense Canada UNCLASSIFIED – APPROVED FOR PUBLIC RELEASE Challenges for a Distributed Collaborative Environment Functioning.
Annual SERC Research Review - Student Presentation, October 5-6, Extending Model Based System Engineering to Utilize 3D Virtual Environments Peter.
Dr. Mark Askelson | 4149 University Avenue Stop 9006, Grand Forks, ND phone | fax Ganged Phased Array Radar – Risk Mitigation.
1 EVALUATING INTELLIGENT FLUID AUTOMATION SYSTEMS USING A FLUID NETWORK SIMULATION ENVIRONMENT Ron Esmao - Sr. Applications Engineer, Flowmaster USA.
Anticipatory Planning using Execution Monitoring and a Constrained Planning Frontier John M. D. Hill Lieutenant Colonel, U. S. Army Assistant Professor,
NATO VIZ-N/X Custom Ontologies for Expanded Social Network Analysis Amy K. C. S. Vanderbilt, Ph.D. and J. Andrew Skene 4465 Brookfield Corporate Drive,
TRADOC Program Integration Office for
Web-Enabled Decision Support Systems
HPC use in Testing Ad Hoc Wireless Sensor Networks
Military Logistics Cargo Distribution Management for the Next Conflict Chris Ballard, Wyly Gilfoil, Kathy Lau, Jay Miseli, Scott Ostrowski, Sebastien Prangere,
Headquarters U. S. Air Force I n t e g r i t y - S e r v i c e - E x c e l l e n c e © 2008 The MITRE Corporation. All rights reserved From Throw Away.
Salim Hariri HPDC Laboratory Enhanced General Switch Management Protocol Salim Hariri Department of Electrical and Computer.
Parallel and Distributed Simulation Introduction and Motivation.
Comparative Navigation System for Collaborative Project The 15-th International Conference in Central Europe on Computer Graphics, Visualization and Computer.
Parallel and Distributed Simulation Introduction and Motivation.
July, 6, 2004 QoS and Dynamic Systems Workshop, ICPADS S. Olariu1, K. Maly2, E. C. Foudriat3 and S. M. Yamany4 {1,2,3}Department of Computer Science,
Large Scale Visualization Environment and Decision-Centered Visualization Cdr. Robert Barton Naval Undersea Warfare Center Newport, Rhode Island USA L.
Overview of Information and Signal Processing Program 24 January 2007 Liyi Dai, Program Manager Computing & Information Sciences Division Mathematical.
IS Metrics for C2 Processes Working Group 3 Brief Team Leaders: Steve Soules Dr. Mark Mandeles.
FA50 Qualification Course
Advances in Decision Modeling: The DMSO Vector Lt Col Eileen A. Bjorkman Chief, Concepts Application Division Zach Furness C4I Program Manager 31 July.
Distribution A: Approved for public release; distribution is unlimited Get the right M&S technology to the right place, at the right time, for the Decision.
Week 04 Object Oriented Analysis and Designing. What is a model? A model is quicker and easier to build A model can be used in simulations, to learn more.
Microsoft in Defence Michel van der Bel Vice President Microsoft International.
Pertemuan 16 Materi : Buku Wajib & Sumber Materi :
By CPT Robert L. Crabtree
THE IMPACT OF OSPF ROUTING ON MILITARY MANETS BY ROCCO LUPOI UNDER THE GUIDANCE OF DR. GRANT WIGLEY THESIS - BACHELOR OF COMPUTER SCIENCE (HONOURS) - LHIS.
JNTC Joint Management Office
TRADOC Designing & Building the Future Army
8th CGF & BR Conference May 1999 Copyright 1999 Institute for Simulation & Training Deriving Priority Intelligence Requirements for Synthetic Command.
Family Readiness Group Overview. Objectives of Family Readiness Group (FRG) Overview Define Family Readiness Define the mission and role of the FRG Review.
System of Systems Observations and Hypotheses George E. Pickett, Vice President.
Army Aviation in MOUT.
The marine air ground task force (magtf)
A Methodology to Support Anticipatory Planning John M. D. Hill John R. “Buck” Surdu Udo W. Pooch.
Previous Slide TRADOC DCSINT Office of the Deputy Chief of Staff for Intelligence U.S. Army Training and Doctrine Command TRADOC DCSINT.
Applicability - Analysis Plan Analysis Plan Part 1: Identification of the technological characteristics –Technology strategy –Competitive priorities of.
Accelerated Adaptation Evolution The learning contest between the IDF and its adversaries ( ) Hezbollah [aided by Iran], Hamas, Islamic Jihad (Gaza),
United States Army Combined Arms Center A next generation simulation architecture supporting both Computer Generated Forces (CGF) and SAF operations Provides.
Interaction and Animation on Geolocalization Based Network Topology by Engin Arslan.
Tactical Decision Games
Architecture Tool Vendor’s Day
Role and Plan - Demand Demand Team assesses the scope of this capability and the levels of usefulness. Step 1 – Read relevant articles and After-Action.
Using An Isolated Network to Teach Advanced Networks and Security
Existing Army Systems Force XXI Battle Command Brigade-and-Below (FBCB2) Provides battle command and situational awareness information Digitally networks.
Presentation transcript:

Information Flow: Tactical Network Design and Bandwidth Management University XXI Texas A&M University University of Texas United States Army

Texas A&M University - U.S. Army Agenda Introduction –Motivation –Collaboration –People Background –Tactical Communications Network –Command Posts –Army Battle Command Systems Problem and Requirements Implementation Conclusion

Texas A&M University - U.S. Army Introduction - Motivation The United States Army wants to improve the use of information systems to achieve tactical advantage over potential adversaries Various information systems are already deployed with Army units, and as the Army modernizes its forces and updates its doctrine, new uses for these existing information systems are developed Simultaneously, the Army is investigating applications of new and emerging information technologies in the tactical arena These new capabilities and new systems place increasing and uncoordinated demands on the tactical data network, resulting in a bandwidth management crisis

Texas A&M University - U.S. Army Introduction - Collaboration Force XXI –The U.S. Army’s vision of future heavy-force combat –Focus on information dominance University XXI –Cooperative effort between Texas A&M University, The University of Texas, and the U.S. Army –Apply the fruits of academic knowledge, experience, and research in information systems to the military domain “Know your enemy, know yourself, and in a hundred battles you will never be in peril.” - Sun Tzu

Texas A&M University - U.S. Army Introduction - People The Principal Researchers represent a unique convergence of military and information technology experience –LTC John M. D. Hill - Armor Officer, Simulation, Graphics and GUIs, Planning Support Systems –LTC Curtis A. Carver, Jr. - Signal Officer, Networks, Adaptive Information Systems –MAJ John R. “Buck” Surdu - Infantry Officer, Acquisition Corps, Simulations, Planning Support Systems –Dr. Udo W. Pooch - Former Marine Corps, extensive experience in Simulation, Networks, Information Systems –Mr. Willis Marti - Former Army, extensive Information Systems implementation experience

Texas A&M University - U.S. Army Background - Tactical Communications Network Mobile Subscribe Equipment (MSE) components and links –Node Center (NC) –Large Extension Node (LEN) –Small Extension Node (SEN) V1 model V2 model –High-Speed MUltipleXer Card (HSMUX) Communications Architecture (MSE)

Texas A&M University - U.S. Army Background - Command Posts Three division command posts plus a support command: –Assault CP (DTAC) - two SENs –Main CP (DMAIN) - two SENs –Rear CP (DREAR) - connects through the LEN –Division Support Command - connects through the LEN Three Maneuver Brigades plus two separate brigades –Each Brigade TOC and Brigade Rear CP gets one SEN Three Separate Battalions (MI, ADA, Signal) –Each get one SEN Tactical Entities MAINREAR

Texas A&M University - U.S. Army Background - Army Battle Command System (ABCS) “A system of systems” - merged stovepipes –Maneuver: Maneuver Control System (MCS) –Intelligence: All Sources Analysis System (ASAS) –Fire Support: Advanced Field Artillery Tactical Data System (AFATDS) –Logistics: Combat Service Support Computer System (CSSCS) –Air Defense: Air and Missile Defense Planning and Control System (AMDPCS) –Others MCS ASASAFATDSCSSCS Information Systems

Texas A&M University - U.S. Army Put it all together … Communications Architecture (MSE)Tactical Entities MAINREAR Operational Conditions MCS ASASAFATDSCSSCS Information Systems

Texas A&M University - U.S. Army The Problem There is no mechanism for prioritizing the information flows or for determining the best allocation of available communication system resources to support particular operational conditions. There is no ability to examine the impact of new capabilities or new information systems –High-resolution network simulation are too low-level and don’t account for the flows from information systems –Can’t attribute network traffic to specific flows between information systems. Can’t afford to send the Division communications structure, Command Posts, and information systems to the field every time an experiment is desired.

Texas A&M University - U.S. Army The Requirements The planners need a tool for designing the tactical data network to meet the expected data bandwidth requirements of current and future battlefield information systems. This tool must be able to simulate the flows on the data network over time for different communications configurations and different operational conditions The tool must have a good model of the information flows to be able to predict network performance.

Texas A&M University - U.S. Army The Implementation - Summary Component Modeling –Tactical Data Network at the message aggregate level –ABCS Systems as flow producers –Tactical Entities change missions based on operational condition The Information Flow Drivers - between systems –Routinely generated information flows For example, ASAS database download every two hours –Other information flow patterns Modeled as distributions, table-lookup, or burst schedule. Statistics Visualization and Capture –Planner can observe the effects of changes on the overall system and “drill-down” to detailed statistical information.

Texas A&M University - U.S. Army The Implementation - Summary Flexibility –Segregation of Information Systems, Tactical Entities, and Communications Network –Flow drivers are parameterized to allow configuration of each flow, and the system allows for replacement by more accurate models as real data is captured –The planner can use the graphical user interface to change the setup of any component in the system

Texas A&M University - U.S. Army Screen Capture

Texas A&M University - U.S. Army Conclusion The Information Flow tool will enable planners to rapidly determine viable configurations based on actual mission requirements and current systems capability New and proposed systems can be added to the model and planners can determine the effects on the overall system This will result in more effective utilization of the available bandwidth and assist in determining prioritization of information flow in the future

Texas A&M University - U.S. Army Questions? If we have time … fire away! Otherwise: – { hillj | carverc | surdu } – –{ hillj | carverc | surdu | pooch