Scalable Clustering of Internet Paths by Shared Congestion

— Internet paths sharing the same bottleneck can be identified using several shared congestion detection techniques. However, all of these techniques have been designed to detect shared congestion between a pair of paths. To cluster N paths by shared congestion, a straightforward approach of using pairwise tests would require O(N2 ) time complexity. In this paper, we present a scalable approach to cluster Internet paths based on DCW (Delay Correlation with Wavelet denoising) which does not require a common end point between paths. We present a function to map each path’s measurement data into a point in a multidimensional space such that points are close to each other if and only if the corresponding paths share congestion. Because points in the space are indexed using a tree-like structure, the computational complexity of clustering N paths can be reduced to O(N log N). The indexing overhead can be further improved by reducing dimensionality of the space through wavelet transform...

• Type: Conference
• Year: 2006
• Where: INFOCOM
• Authors: Min Sik Kim, Taekhyun Kim, YongJune Shin, Simon S. Lam, Edward J. Powers
• Keywords: Communications, INFOCOM 2006, Internet Paths, Paths Share Congestion, Shared Congestion