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Large-Scale Disk Failure Prediction

PAKDD 2020 Competition and Workshop, AI Ops 2020, February 7 – May 15, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Cheng He

    1. Alibaba Group (China), Hangzhou, China

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  2. Mengling Feng

    1. National University of Singapore, Singapore, Singapore

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  3. Patrick P. C. Lee

    1. Chinese University of Hong Kong, Hong Kong, China

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  4. Pinghui Wang

    1. Xi'an Jiaotong University, Xi'an, China

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  5. Shujie Han

    1. Chinese University of Hong Kong, Hong Kong, China

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  6. Yi Liu

    1. Alibaba Group (China), Hangzhou, China

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1261)

Included in the following conference series:

Conference proceedings info: AI Ops 2020.

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Table of contents (13 papers)

  1. Front Matter

    Pages i-x
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  2. An Introduction to PAKDD CUP 2020 Dataset

    • Yi Liu, Shujie Han, Cheng He, Jiongzhou Liu, Fan Xu, Tao Huang et al.
    Pages 1-11

  3. PAKDD 2020 Alibaba AIOps Competition - Large-Scale Disk Failure Prediction: Third Place Team

    • Bo Zhou
    Pages 12-17

  4. A Voting-Based Robust Model for Disk Failure Prediction

    • Manjie Li, Jingjie Li, Ji Yuan
    Pages 18-29

  5. First Place Solution of PAKDD Cup 2020

    • Jie Zhang, Zeyong Sun, Jiahui Lu
    Pages 30-39

  6. Anomaly Detection of Hard Disk Drives Based on Multi-scale Feature

    • Xiandong Ran, Zhou Su
    Pages 40-50

  7. Disk Failure Prediction: An In-Depth Comparison Between Deep Neural Networks and Tree-Based Models

    • Xiang Lan, Pin Lin Tan, Mengling Feng
    Pages 51-63

  8. PAKDD2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction

    • Run-Qing Chen
    Pages 64-73

  9. SHARP: SMART HDD Anomaly Risk Prediction

    • Wei Liu, Yang Xue, Pan Liu
    Pages 74-84

  10. Tree-Based Model with Advanced Data Preprocessing for Large Scale Hard Disk Failure Prediction

    • Qi Wu, Weilong Chen, Wei Bao, Jipeng Li, Peikai Pan, Qiyao Peng et al.
    Pages 85-99

  11. PAKDD2020 Alibaba AI Ops Competition: An SPE-LightGBM Approach

    • Yuanpeng Li, Yaoran Sun
    Pages 100-108

  12. Noise Feature Selection Method in PAKDD 2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction

    • Yifan Peng, Junfeng Xu, Nan Zhao
    Pages 109-118

  13. Characterizing and Modeling for Proactive Disk Failure Prediction to Improve Reliability of Data Centers

    • Tuanjie Wang, Xinhui Liang, Quanquan Xie, Qiang Li, Hui Li, Kai Zhang
    Pages 119-129

  14. Summary of PAKDD CUP 2020: From Organizers’ Perspective

    • Cheng He, Yi Liu, Tao Huang, Fan Xu, Jiongzhou Liu, Shujie Han et al.
    Pages 130-142

  15. Back Matter

    Pages 143-143
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About this book

This book constitutes the thoroughly refereed post-competition proceedings of the AI Ops Competition on Large-Scale Disk Failure Prediction, conducted between February 7th and May 15, 2020 on the Alibaba Cloud Tianchi Platform. A dedicated workshop, featuring the best performing teams of the competition, was held at the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, in Singapore, in April 2019. Due to the COVID-19 pandemic, the workshop was hosted online.

This book includes 13 selected contributions: an introduction to dataset, selected approaches of the competing teams and the competition summary, describing the competition task, practical challenges, evaluation metrics, etc.

Editors and Affiliations

  • Alibaba Group (China), Hangzhou, China

    Cheng He, Yi Liu

  • National University of Singapore, Singapore, Singapore

    Mengling Feng

  • Chinese University of Hong Kong, Hong Kong, China

    Patrick P. C. Lee, Shujie Han

  • Xi'an Jiaotong University, Xi'an, China

    Pinghui Wang

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