An integrated congestion management architecture for Internet hosts
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Detecting shared congestion of flows via end-to-end measurement
IEEE/ACM Transactions on Networking (TON)
Robust identification of shared losses using end-to-end unicast probes
ICNP '00 Proceedings of the 2000 International Conference on Network Protocols
A wavelet-based approach to detect shared congestion
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
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Most existing techniques detecting shared congestion paths are based on pair-wise comparison of paths with a common source or destination point. It is difficult to extend them to cluster paths with different sources and destinations. In this paper, we propose a scalable approach to cluster shared congestion paths based on PCA. This algorithm maps the delay measurement data of each path into a point in a new, low-dimensional space based on the factor loading matrix in PCA, which reflect correlation between paths. In this new space, points are close to each other if the corresponding paths share congestion. Then, the clustering analysis is applied to these points so as to identify shared congestion paths accurately. This algorithm is evaluated by NS2 simulations. The results show us that this algorithm has high accuracy.