Analysis of communication network surveillance using functional ANOVA model with unequal variances

Analysis of simulation result plays an important role in helping decision-making when simulation modeling is used as an approach to investigate complex systems. Analysis of variance (ANOVA) is a popular statistical technique for analyzing simulation results when various designs of simulation experiments are implemented and investigated. However, conventional ANOVA technique is based on the assumption of homogeneous variances of output data, which may not be realistic for data coming from the real-world complex systems. The existence of heterogeneous structures of data coming from complex systems requires a more reliable analysis method, in order to analyze such data. In this paper, a functional ANOVA model with unequal variances is proposed for meeting this goal. The proposed model aims to better capture the heterogeneous data structure that is caused by various experimental simulation setups. The applicability of the proposed method is illustrated by using simulated communication network traffic data. Our work contributes to the development of new approaches for analysis of simulation and real-world complex systems data with heterogeneous structures. The proposed method can be useful for defense problems, e.g. for analysis of communication network surveillance or for the purpose of improving the operational efficiency.