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Collaborative Response to Disruption Propagation (CRDP)Phuc V Nguyen (8779382) 01 May 2020 (has links)
<p><a>Disruptive events during recent
decades have highlighted the vulnerabilities of complex systems of systems to
disruption propagation: </a>Disruptions that start in one part of a system and can propagate
to other parts. Such examples include: Fire spreading in building
complexes and forests; plant/crop diseases in agricultural production systems;
propagating malware in computer networks and cyber-physical systems; and
disruptions in supply networks. The impacts of disruption propagation are
devastating, with fire causing annual US$23 billion loss in the US alone, plant
diseases/crop reducing agricultural productivity 20% to 40% annually, and
computer malware causing up to US$2.3 billion loss per event (as a conservative
estimate). These problems, the response to disruption propagation (<a>RDP</a>)
problems, are challenging due to the involvement of different problem aspects
and their complex dynamics. To better design and control the responses to
disruption propagation, a general framework and problem-solving guideline for
the RDP problems is necessary.<br></p><p><br></p>
<p> </p>
<p>To address the
aforementioned challenge, this research develops the Collaborative Response to
Disruption Propagation (<a>CRDP</a>) unifying framework to classify,
categorize, and characterize the different aspects of the RDP problems. The
CRDP framework allows analogical reasoning across the different problem
contexts, such as the examples mentioned above. Three main components
applicable to the investigate RDP problems are identified and characterized:
(1) The client system as the victims; (2) The response mechanisms as the
rescuers/protectors; and (3) The disruption propagation as the
aggressors/attackers. This allows further characterization of the complex
interactions between the components, which augments the design and control
decisions for the response mechanisms to better respond to the disruptions. The
new Covering Lines of Collaboration (<a>CLOC</a>) principle,
consisting of three guidelines, is developed to analyze the system state and
guide the response decisions. The first CLOC guideline recommends the network
modeling of potential disruption propagation directions, creating a complex
network for better situation awareness and analysis. The second CLOC guideline
recommends the analysis of the propagation-restraining effects due to the
existence of the response mechanisms, and utilizing this interaction in
optimizing response decisions. The third CLOC guideline recommends the
development of collaboration protocols between the response decisions to
maximize the coverage of response against disruption propagation.</p><p><br></p>
<p> </p>
<p>The CRDP framework
and the CLOC principle are validated with three RDP case studies: (1) Detection
of unknown disruptions; (2) Strategic prevention of unexpected disruptions; (3)
Teaming and coordination of repair agents against recurring disruptions.
Formulations, analytics, and protocols specific to each case are developed. TIE/CRDP, a new version of
the Teamwork Integration Evaluator (<a>TIE</a>) software, is developed
to simulate the complex interactions and dynamics of the CRDP components, the
response decision protocols, and their performance. The evaluator is
capable of simulating and evaluating the complex interactions and dynamics of
the CRDP components and the response decision protocols. <a>Experiment results indicate that advanced CLOC-based decisions significantly
outperform the baseline and less advanced protocols for all three cases, with
performance superiority of 9.7-32.8% in case 1; 31.1%-56.6% in case 2; 2.1%-12.1%
for teaming protocols, and at least 50% for team coordination protocols in case
3.</a></p>
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