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The RPCA model has achieved good performances in various applications. However, two defects limit its effectiveness. Firstly, it is designed for dealing with data in matrix form, which fails to exploit the structure information of higher order tensor data in some pratical situations. Secondly, it adopts L1-norm to tackle noise part which makes it only valid for sparse noise. In this paper, we propose...
Clean drinking water and safe water supply is vital to our life. Recent advances in technologies have made it possible to deploy smart sensor networks in large water distribution networks to monitor and identify the water quality online. In such a large-scale real-time monitoring application, large amounts of data stream out of multiple concurrent sensors continuously. In this paper, we present a...
In many sensor network applications, it is essential to get the data distribution of the attribute value over the network. Such data distribution can be got through clustering, which partitions the network into contiguous regions, each of which contains sensor nodes of a range of similar readings. This paper proposes a method named Distributed, Hierarchical Clustering (DHC) for online data analysis...
We present the I3DC system prototype, which constructs the cube for tens of millions of data items within milliseconds, and provides high-quality cube visualization as well as highly-interactive OLAP operations. Our approach is based on a novel blending-as-aggregation (BAA) algorithm that maps distributive OLAP aggregations to the intrinsic rendering mechanisms of the GPU. Our system runs entirely...
Large flash disks have become an attractive alternative to magnetic hard disks, due to their high random read performance, low energy consumption and other features. However, writes, especially random writes, on the flash disk are inherently much slower than reads because of the erase-before-write mechanism. To address this asymmetry of read-write speeds in indexing on the flash disk, we propose the...
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