PREFAIL | REINFORCEMENT LEARNING FOR PREDICTIVE FAILURE-DETECTION AND PROACTIVE DATA MANAGEMENT ON DIGITAL STORAGE SYSTEMS

Summary
As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. Nevertheless, Internet applications and services remain prone to inevitable hardware failures, that lead to data losses and increased maintenance costs. The primary problem lies with the cost of implementing data redundancy by constantly adding expensive hardware to cater to the needs of traditional data replication approaches (e.g. by always keeping copies of a file on multiple servers).

With the assistance of an Innovation Associate specializing in Machine Learning, Algolysis Ltd aspires to extend its cloud-based storage device monitoring service (DriveNest - www.drivenest.com) with a robust state-of-the-art failure prediction engine. Reliably identifying soon-to-fail storage devices can be a transformative capability across the ICT sector, as a range of proactive data management and mitigation services can be built on top.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/957149
Start date: 01-10-2020
End date: 28-02-2022
Total budget - Public funding: - 84 700,00 Euro
Cordis data

Original description

As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. Nevertheless, Internet applications and services remain prone to inevitable hardware failures, that lead to data losses and increased maintenance costs. The primary problem lies with the cost of implementing data redundancy by constantly adding expensive hardware to cater to the needs of traditional data replication approaches (e.g. by always keeping copies of a file on multiple servers).

With the assistance of an Innovation Associate specializing in Machine Learning, Algolysis Ltd aspires to extend its cloud-based storage device monitoring service (DriveNest - www.drivenest.com) with a robust state-of-the-art failure prediction engine. Reliably identifying soon-to-fail storage devices can be a transformative capability across the ICT sector, as a range of proactive data management and mitigation services can be built on top.

Status

CLOSED

Call topic

INNOSUP-02-2019-2020

Update Date

27-10-2022
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Horizon 2020
H2020-EU.2. INDUSTRIAL LEADERSHIP
H2020-EU.2.3. INDUSTRIAL LEADERSHIP - Innovation In SMEs
H2020-EU.2.3.2. Specific support
H2020-EU.2.3.2.2. Enhancing the innovation capacity of SMEs
H2020-INNOSUP-2019-02
INNOSUP-02-2019-2020 European SME innovation Associate - pilot