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End-to-end network monitoring is essential to ensure transmission quality for Internet applications. However, in large-scale networks, full-mesh measurement of network performance between all transmission pairs is infeasible. As a newly emerging sparsity representation technique, matrix completion allows the recovery of a low-rank matrix using only a small number of random samples. Existing schemes...
Matrix completion has emerged very recently and provides a new venue for low cost data gathering in WSNs. Existing schemes often assume that the data matrix has a known and fixed low-rank, which is unlikely to hold in a practical monitoring system such as weather data gathering. Weather data varies in temporal and spatial domain with time. By analyzing a large set of weather data collected from 196...
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