The DEBS 2024 Grand Challenge: Telemetry Data for Hard Drive Failure Prediction

被引：1

作者：

De Martini, Luca ^{[1
]}

Tahir, Jawad ^{[2
]}

Doblander, Christoph ^{[2
]}

Frischbier, Sebastian ^{[3
]}

Margara, Alessandro ^{[1
]}

机构：

[1] Politecn Milan, Milan, Italy

[2] Tech Univ Munich, Munich, Germany

[3] Allianz Global Investors GmbH, Frankfurt, Germany

来源：

PROCEEDINGS OF THE 18TH ACM INTERNATIONAL CONFERENCE ON DISTRIBUTED AND EVENT-BASED SYSTEMS, DEBS 2024 | 2024年

关键词：

event processing; stream processing; data processing; data analytics; benclunark; challenge; performance evaluation;

D O I：

10.1145/3629104.3672538

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The DEBS Grand Challenge (GC) is a programming competition integrated into the annual ACM International Conference on Distributed and Event -Based Systems (DEBS) since DEBS 2011. The DEBS GC 2024 edition focuses on analyzing real-world telemetry data about over 200k hard drives in data centers. The goal of the challenge is to continuously compute clusters of similar drives as new data is received. This kind of analysis may be relevant to quickly identify groups of drives with a high probability of failure and enact predictive maintenance strategies. The submitted solutions are evaluated based on their design, performance, efficiency, ease of reuse, fault -tolerance, and adaptation to different problems. This paper describes the domain of telemetry data for hard drives, the data set used in the challenge, the specific problem formulation, and CHALLENGER platform used to evaluate the submissions.

引用

页码：223 / 228

页数：6

共 26 条

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