Abstract:The available bandwidth is a crucial metric of networks performance which is applied in congestion control, route selection, traffic analysis and QoS management. PathChirp is a well-known tool to estimate available bandwidth based on an approach of self-induced congestion, which exponentially increases the rate of probing packets in each packet train. But the inappropriate gaps of probing rates often result in a large deviation of estimated available bandwidth. In order to solve this problem, we propose HybChirp, an active probing tool which uses linearly spaced probing packets (lin-chirps) and exponentially spaced probing packets (exp-chirps) in combination. HybChirp improves PathChirp by adopting the hybrid of lin-chirps and exp-chirps, while inherits the advantages of PathChirp such as the short convergence time and low overhead. The NS-2 simulation results have shown that HybChirp outperforms PathChirp and Pathload in terms of accuracy, overhead, convergence time and adaptivity.
We propose a new feature called Global Reoccurrence Measure for extracting keywords from a document. It expresses the characteristic of keywords that they reoccur frequently in local areas, and have wide coverage in a document. Experiments show that the global reoccurrence measure can improve the performance of keyword extraction. We also propose a new metric called extraction quality for performance evaluation of keyword extraction.
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