Impact of Traffic Sampling On Lrd Estimation

Network traffic sampling is an effective method for understanding the behavior and dynamics of a network, being essential to as- sist network planning and management. Tasks such as controlling Service Level Agreements or Quality of Service, as well as planning the capacity and the safety of a network can benefit from traffic sampling advantages. The main objective of this paper is focused on evaluating the impact of sampling network traffic on: (i) achieving a low-overhead estimation of the network state and (ii) assessing the statistical properties that sampled network traffic presents regarding the eventual persistence of Long-Range Dependence (LRD). For that, different Hurst parameter estimators have been used. Facing the impact of LRD on network congestion and traffic engineering, this work will help clarify the suitability of distinct sampling techniques in accurate network analysis.