@inproceedings{327d7d9d453241878d2d949465eabaae,
title = "Data stream prediction in distributed stream processing environment",
abstract = "With the wide adoption of distributed stream processing, the requirement of guaranteeing QoS has been raised to a new standard. Since node load influences QoS directly, it is a hotspot of research. Through analyzing the relationship between input data stream and load of physical node this paper abstracted a local node model from traditional distributed stream processing network. Based on this model, a new data stream prediction algorithm grounded on a classic machine learning algorithm - Share Algorithm - is proposed. The new algorithm uses recent data stream as the prediction resource and efficiently accomplishes the prediction of single nodes in the future period. Our experiments show that 73\% of predictions can achieve the accuracy more than 90\% with some common data traces.",
keywords = "Data, Distributed stream processing, Prediction",
author = "Jie Chen and Yuanqiang Huang and Zhongzhi Luan",
year = "2012",
doi = "10.1049/cp.2012.1085",
language = "英语",
isbn = "9781849195379",
series = "IET Conference Publications",
number = "598 CP",
pages = "747--750",
booktitle = "International Conference on Automatic Control and Artificial Intelligence, ACAI 2012",
edition = "598 CP",
note = "International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 ; Conference date: 03-03-2012 Through 05-03-2012",
}