SmtRPTG: Highly-Efficient Monitoring Scheme to Capture Network Status Changes Accurately

As network monitoring is crucial for ensuring the performance of network operations, one key challenge is how to optimize the tradeoff between its overheads and accuracy. This paper proposes a smart reporting mechanism, namely SmtRPTG, which continuously optimizes the scheme of network status collecting and reporting to properly balance the tradeoff. SmtRPTG estimates the distributions of status data of various types based on sampled results, and lets network elements make local decisions on whether and what type of status data should be reported based on the estimations. We formulate a probabilistic model with hidden variables, based on which an algorithm is designed to estimate data distributions for SmtRPTG. Extensive simulations verify the effectiveness of our proposal on balancing the tradeoff between overheads and accuracy of network monitoring.