Titlebook: Algorithms and Architectures for Parallel Processing; 18th International C Jaideep Vaidya,Jin Li Conference proceedings 2018 Springer Natur

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Efficient Algorithms of Parallel Skyline Join over Data Streamsowledge, this is the first paper that addresses parallel computing of . over multiple data streams. Extensive experimental evaluations on real and synthetic data sets show that the algorithms proposed in this paper provide large gains over the state-of-the-art serial algorithm of . over data streams

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An Active Learning Based on Uncertainty and Density Method for Positive and Unlabeled DataSAL) automatically annotating some confident unlabeled samples in the each iteration is proposed to reduce the number of manually annotated samples. Experimental results indicate that our proposed method is competitive with other similar methods.

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Network-Aware Grouping in Distributed Stream Processing Systemson clusters of commodity hardware. Existing workload grouping strategies in a DSP system can be classified into four categories (i.e. raw and blind, data skewness, cluster heterogeneity, and dynamic load-aware). However, these traditional stream grouping strategies do not consider network distance b

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vPlacer: A Co-scheduler for Optimizing the Performance of Parallel Jobs in Xendays. Currently, the existing schedulers of Xen are initially targeting at serial jobs, which achieves a remarkable utilization of computer hardware and impressive overall performance. However, the virtualized systems are expected to accommodate both parallel jobs and serial jobs in practice, and re

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Document Nearest Neighbors Query Based on Pairwise Similarity with MapReducevariability. Among them, how to organize plenty of web pages and retrieval information needed is a critical one. An important notion is document classification, in which nearest neighbors query is the key issue to be solved. Most parallel nearest neighbors query methods adopt Cartesian Product betwe

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