Abstract

In the high-throughput scientific applications or researches, the end-to-end high performance data transferring is a critical issue in network and end-systems. If the performance of data transfer were not guaranteed, their researches couldnt achieve successful results and even more the researches couldnt start to do. In order to cope with the complex fault of the end-to-end transmission performance, we proposed the end-to-end network performance management framework based on case-based reasoning with the case library and multi-agent integrated with perfSONAR. We validated the case retrieving process with similarity measure and the real case that results from the performance degradation in the campus backbone segment.

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