TY - GEN
T1 - Using social network analysis to quantify interoperability in a large system of systems
AU - Enos, James R.
AU - Nilchiani, Roshanak
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/27
Y1 - 2017/7/27
N2 - The Department of Defense (DoD) manages a large, complex system of systems that must operate together on the battlefield to deliver value. However, it is difficult to understand the network wide impacts of changes to the system of systems. The DoD has had difficulty managing this system of systems due to the scale and complexity of the network and traditional systems engineering tools do not provide necessary insights for DoD decision makers. This paper proposes applying social network analysis to understand the interoperability associated with the DoD system of systems. It applies several centrality metrics to a network of Major Defense Acquisition Programs (MDAPs) to quantify the interoperability of individual systems within the system of systems. Specifically, it examines the differences between the degree, closeness, and eigenvector centrality metrics to identify which metric best represents the interoperability of individual systems.
AB - The Department of Defense (DoD) manages a large, complex system of systems that must operate together on the battlefield to deliver value. However, it is difficult to understand the network wide impacts of changes to the system of systems. The DoD has had difficulty managing this system of systems due to the scale and complexity of the network and traditional systems engineering tools do not provide necessary insights for DoD decision makers. This paper proposes applying social network analysis to understand the interoperability associated with the DoD system of systems. It applies several centrality metrics to a network of Major Defense Acquisition Programs (MDAPs) to quantify the interoperability of individual systems within the system of systems. Specifically, it examines the differences between the degree, closeness, and eigenvector centrality metrics to identify which metric best represents the interoperability of individual systems.
KW - interoperability
KW - social network analysis
KW - system of systems engineering
UR - http://www.scopus.com/inward/record.url?scp=85028569769&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028569769&partnerID=8YFLogxK
U2 - 10.1109/SYSOSE.2017.7994932
DO - 10.1109/SYSOSE.2017.7994932
M3 - Conference contribution
AN - SCOPUS:85028569769
T3 - 2017 12th System of Systems Engineering Conference, SoSE 2017
BT - 2017 12th System of Systems Engineering Conference, SoSE 2017
T2 - 12th System of Systems Engineering Conference, SoSE 2017
Y2 - 18 June 2017 through 21 June 2017
ER -