Predictive Resource Management of Multiple Monitoring Applications

We propose a predictive resource management scheme for network monitoring systems that can proactively shed excess load while maintaining the accuracy of monitoring applications within bounds defined by the operator. The main novelty of our scheme is that it considers monitoring applications as black boxes, with arbitrary (and highly variable) input traffic and processing cost. This way, the monitoring system preserves a high degree of flexibility, increasing the range of applications and network scenarios where it can be used. We implemented our load-shedding-based resource management scheme in an existing network monitoring system and deployed it in a large research and educational network. We present experimental evidence of the performance and robustness of our system with multiple concurrent monitoring applications during long-lived executions and using real-world traffic traces.