Abstract

Presents a scalable protocol for conducting periodic probes of network performance in a way that minimizes collisions between separate probes. The goal of the protocol is to enable active performance monitoring of large-scale distributed computational systems and networks. We use the protocol to generate time series of measurement data that are then exposed to numerical forecasting models when a prediction of network performance is required. We present the protocol and demonstrate its effectiveness using the Network Weather Service -a tool for dynamically predicting network, CPU, memory and storage performance.

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