Rate-Sensitive Load Shedding in Data Stream Systems(Data Mining)

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概要

• 論文の詳細を見る

• Traditional load shedding algorithms for data stream systems calculate current operator selectivity over several run periods and use them to determine where to shed load during the next run period. In this paper, we show that the current selectivity may change due to the implementation of load shedding. Our algorithm, called RLS, determines the optimum drop location by these changed selectivity rather than those precalculated values. Simulation results demonstrate that RLS achieves higher accuracy than traditional algorithms.

• 社団法人電子情報通信学会の論文
• 2007-07-01

著者

• FAN Xun

  Department of Electronic Engineering, Shanghai Jiaotong University

• Fan Xun

  Department Of Electronic Engineering Shanghai Jiao Tong University

• Fan Xun

  Department Of Electronics And Engineering Shanghai Jiaotong University

• YIN Zhiwu

  Department of Computer Science and Engineering, Shanghai Jiaotong University

• HUANG Shangteng

  Department of Computer Science and Engineering, Shanghai Jiaotong University

• Huang Shangteng

  Department Of Computer Science And Engineering Shanghai Jiaotong University

• Yin Zhiwu

  Department Of Computer Science And Engineering Shanghai Jiaotong University

関連論文

• Least-Squares Zero-Forcing User-Ordered Successive Interference Cancellation for Multi-User STBC Systems(Mobile Communication, Wireless Technologies and Computational Electromagnetics)
• Rate-Sensitive Load Shedding in Data Stream Systems(Data Mining)
• Newly-Built Iterative Receiver and Hardware Implementation for V-BLAST(Wireless Communication Technologies)
• Incorporating Metadata into Data Mining with Ontology(Data Mining)

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