A Power-Aware Online Scheduling Algorithm for Streaming Applications in Embedded MPSoC
2011As application complexity grows, embedded systems move to multiprocessor architectures to cope with the computation needs. The issue formultiprocessor architectures is to optimize the processing resources usage and power consumption to reach a higher energy efficiency. These optimizations are handled by scheduling techniques.
Tanguy Sassolas +3 more
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A new online field feature selection algorithm based on streaming data
Journal of Ambient Intelligence and Humanized Computing, 2018The rapid development of Internet technology derived out a massive network text data. Therefore, how to classify the massive text data efficiently has important theoretical significance and application value. In order to acquire accurate classification results, the process has been divided into two parts.
Zhenjiang Zhang +4 more
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Online stream clustering using density and affinity propagation algorithm
2013 IEEE 4th International Conference on Software Engineering and Service Science, 2013In order to improve the data stream clustering accuracy and effectiveness, the paper proposes an efficient data stream clustering algorithm based on affinity propagation and density methods (APDenStream). The algorithm adopts online/offline two stage process framework, by using micro-cluster decay density to reflect the evolution information and using ...
null Jian-Peng Zhang +3 more
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An Online Anomalous Time Series Detection Algorithm for Univariate Data Streams
2013We address the online anomalous time series detection problem among a set of series, combining three simple distance measures. This approach, akin to control charts, makes it easy to determine when a series begins to differ from other series. Empirical evidence shows that this novel online anomalous time series detection algorithm performs very well ...
Huaming Huang +2 more
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Semi-supervised Learning Algorithm for Online Electricity Data Streams
2014Recent developments in electricity market deregulation, the prices are not fixed. In such application, class labels are not available directly and potentially valuable information is lost. A learning model of electricity demand and prices needs to be adaptive for dynamic changes in massive data streams. This paper presents adaptive building of learning
Pramod Patil +2 more
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An Unsupervised Online Streaming Feature Selection Algorithm with Density Peak Clustering
2023 IEEE International Conference on Networking, Sensing and Control (ICNSC), 2023Yu Song, Zhigang Liu 0006
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RHDOFS: A Distributed Online Algorithm Towards Scalable Streaming Feature Selection
IEEE Transactions on Parallel and Distributed Systems, 2023Chuan Luo 0001 +5 more
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Geometric Approximation Algorithms in the Online and Data Stream Models.
2008The online and data stream models of computation have recently attracted considerable research attention due to many real-world applications in various areas such as data mining, machine learning, distributed computing, and robotics. In both these models, input items arrive one at a time, and the algorithms must decide based on the partial data ...
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Streaming Algorithms for Online Selection Problems.
CoRR, 2020José Correa 0001 +4 more
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A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022Di Wu, Xin Luo, Yi He
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