The statistical analyses indicate that the measured traffic traces from the packet networks often contain non-stationary effects. In these cases several popular tests for long-range dependence and/or stationarity can result in wrong conclusions and unreliable estimate of the Hurst parameter. In this paper non-stationarities are modeled as the trends and/or level shifts in Internet traffic data. MMPP-Based Hierarchical Model simulation data are used for stationarity tests. Application of testing results are integrated into network resource allocation function as a Partially Observable Markov Decision process.