Performance modeling for data monitoring services in smart grid: A network calculus based approach

This paper focuses on solving the modeling issues of monitoring system service performance based on the network calculus theory. First, we formulate the service model of the smart grid monitoring system. Then, we derive the flow arrival curve based on the incremental process related functions. Next, we develop flow arrival curves for the case of the incremental process being a fractional Gaussian process, and then we obtain the generalized Cauchy process. Three technical theorems related to network calculus are presented as our main results. Mathematically, the variance of arrival flow for the continuous time case is derived. Assuming that the incremental process of network flow is a Gaussian stationary process, and given the auto-correlation function of the incremental process with violation probability, the formula of the arrival curve is derived. In addition, the overall flow variance under the discrete time case is explicitly derived. The theoretical results are evaluated in smart grid applications. Simulations indicate that the generalized Cauchy process outperforms the fractional Gaussian process for our considered problem.