Adaptive sampling methods for network performance metrics measurement and evaluation in MPLS-based IP networks

In this paper, we propose, develop and evaluate a new adaptive sampling scheme for monitoring and measuring network performance metrics in MPLS-based IP networks supporting real time applications. The paper is focused on investigating the mechanisms that can adaptively adjust the parameters of the sampling technique based on the estimated traffic rate. The performance of the proposed technique is compared with conventional sampling method by conducting simulation experiments using voice traffic patterns. Simulation results are presented to illustrate that adaptive sampling provides the potential for better monitoring, control, and management of high-performance networks with higher accuracy, lower overhead, or both.