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Online End-to-End Quality of Service Monitoring for Service Level Agreement Verification

Service-level-agreement (SLA) monitoring measures network quality-of-service (QoS) parameters to evaluate whether the service performance complies with the SLAs. It is becoming increasingly important for both Internet service providers (ISPs) and their customers. However, the rapid expansion of the Internet makes SLA monitoring a challenging task. As an efficient method to reduce both complexity and overheads for QoS measurements, sampling techniques have been used in SLA monitoring systems. In this paper, a novel adaptive stratified sampling strategy is developed based on the stratified sampling with optimum allocation to make the QoS monitoring less intrusive and more efficient. Simulations using real traffic traces are conducted, which show that the proposed algorithm achieves better performance than systematic sampling and Poisson sampling