Date of Award

Spring 2012

Document Type


Degree Name

Doctor of Philosophy (PhD)


Engineering Management

Committee Director

Ghaith Rabadi

Committee Member

Shannon Bowling

Committee Member

Resit Unal

Committee Member

Sean Deller


With advances in networked communications, the capabilities of command and control (C2) have come to play an increasingly larger role in battlefield success. Within the past two decades a new military strategy has evolved, known as Network-Centric Operations (NCO), which puts information superiority on the frontline. Moreover, the information advantage that is gained through information superiority is translated into a tactical war-fighting advantage.

A research gap has been identified in the investigation of networked combat force configurations in the realm of asymmetric engagements. Specifically, the research question is, how should an information age combat force be networked in order to increase its combat effectiveness in asymmetric engagements with balanced forces? The objective of this research is to identify which performance metrics are best suited in measuring combat effectiveness in the situations of asymmetric engagements with balanced force sizes. In order to reach conclusions on the research objective, a series of experiments have been conducted using a discrete-event simulation based on the Information Age Combat Model (IACM).

The experiments investigate all of the possible engagements for balanced configurations in the format of X-Y-X, ranging from 3 ≤ X ≤ 10, and 3 ≤ Y ≤ X, where X represents the number of sensors and influencers, and Y represents the number of deciders in the network. A total of 1,457,801 unique combat engagement simulations were conducted for data collection. The exact combat network configurations and percentage of wins for both sides were collected for use in the data analysis. Several computer programs were written in order to calculate the various performance metrics associated with each combat configuration. These data, in addition to the win percentages, are used in order to conduct both linear and nonlinear regression models, so that the value of the metrics may be evaluated as combat network performance indicators.

Results indicate that the actual size of the network is a greater predictor for combat performance than any of the metrics calculated from the network configurations. However, it has been determined that network configuration does still play a vital role in combat performance in the case of asymmetric engagements with balanced forces. Moreover, results show that it is possible to configure a network in order to increase its chances of winning in an asymmetric engagement against a larger force size.