Command and Control for Large-Scale Hybrid Warfare Systems

Emerging hybrid threats in large-scale warfare systems require networked teams to perform in a reliable manner under changing mission tactics and reconfiguration of mission tasks and force resources. In this paper, a formal Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, real-time tactic selection, and reliable mission reconfiguration. A mathematically justified networked computing environment is provided called the Augmented Discrete Event Control (ADEC) framework. ADEC is portable and has the ability to provide logical connectivity among all team participants including mission commander, field commanders, war-fighters, and robotic platforms. The proposed C2 structure is developed and demonstrated on a simulation study involving Singapore Armed Forces team with three realistic symmetrical, asymmetrical, and hybrid attack missions. Extensive simulation results show that the tasks and resources of multiple missions are fairly sequenced, mission tactics are correctly selected, and missions and resources are reliably reconfigured in real time.

[1]  Tim Benbow.  Hybrid Warfare: Fighting Complex Opponents from the Ancient World to the Present , 2014 .

[2]  Marina Massei,et al.  Simulation of an urban environment by using intelligent agents within asymmetric scenarios for assessing alternative command and control network-centric maturity models , 2014 .

[3]  Y. F. Zhang,et al.  Cooperative Mission Planning with Multiple UAVs in Realistic Environments , 2014 .

[4]  Randal W. Beard,et al.  Enhanced UAS Surveillance Using a Video Utility Metric , 2013 .

[5]  Timothy R. Puckett.  Rule-based Expert Systems in the Command Estimate: An Operational Perspective , 2012 .

[6]  Peter R. Mansoor,et al.  Hybrid Warfare: Fighting Complex Opponents From The Ancient World To The Present , 2012 .

[7]  W. Marsden.  I and J , 2012 .

[8]  Mark Pflanz,et al.  An Approach to Evaluating Resilience in Command and Control Architectures , 2012, CSER.

[9]  David J. Weeks,et al.  The First US Army Satellite in Fifty Years: SMDC-ONE First Flight Results , 2011 .

[10]  David E. Johnson.  Military Capabilities for Hybrid War: Insights from the Israel Defense Forces in Lebanon and Gaza , 2010 .

[11]  Javad Mohammadpour,et al.  Efficient modeling and control of large-scale systems , 2010 .

[12]  Neville A Stanton,et al.  Using an integrated methods approach to analyse the emergent properties of military command and control. , 2009, Applied ergonomics.

[13]  Frank L. Lewis,et al.  Discrete event command and control for networked teams with multiple missions , 2009, Defense + Commercial Sensing.

[14]  Michael C. Horowitz,et al.  The Future of War and American Military Strategy , 2009 .

[15]  Shu-Hsien Liao,et al.  Problem structuring methods in military command and control , 2008, Expert Syst. Appl..

[16]  Marvin L. Kalb.  The Israeli-Hezbollah War of 2006: The Media as a Weapon in Asymmetrical Conflict , 2007 .

[17]  Rod Thornton,et al.  Asymmetric warfare : threat and response in the twenty-first century , 2007 .

[18]  Frank L. Lewis,et al.  Manufacturing Systems Control Design: A Matrix-based Approach (Advances in Industrial Control) , 2006 .

[19]  William H. J. Manthorpe.  The Emerging Joint System of Systems: A Systems Engineering Challenge and Opportunity for APL , 1996 .

[20]  Joseph J. Suter,et al.  Fifteen years of satellite tracking development and application to wildlife research and conservation , 1996 .

[21]  J. Keegan,et al.  A History of Warfare. , 1995 .

[22]  Li-Min Fu.  CAUSIM: A rule-based causal simulation system , 1991, Simul..

[23]  Harold J. Steudel,et al.  A Decision-Table-Based Processor for Checking Completeness and Consistency in Rule-Based Expert Systems , 1987, Int. J. Man Mach. Stud..

[24]  Edward H. Shortliffe,et al.  An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System , 1982, AI Mag..