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Modern large-scale grid computing for processing advanced science and engineering applications relies on geographically distributed clusters. In such highly distributed environments, estimating the available bandwidth between clusters is a key issue for task scheduling. The authors analyze the performance of two well-known available bandwidth estimation tools, pathload and abget, with the aim of using them in grid environments. The experiments consider the accuracy of the estimation, the convergence time, their level of intrusion in the grid links, and the ability to handle multiple simultaneous estimations. Overall, pathload represents a good solution to estimate available bandwidth in grid environments.
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