A data-assisted reliability model for carrier-assisted cold data storage systems. (April 2020)

• Record Type: Journal Article
• Authors: Arslan, Suayb S.; Peng, James; Goker, Turguy
• Is Part Of: Reliability engineering & system safety. Volume 196(2020)
• Publication Date: 2020-04
• Subjects: Cold data storage -- Non-homogenous Markov model -- Reliability -- Availability -- Simulation -- Aging -- Archive; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2019.106708
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Cold data storage systems include carrier assistance to move/read/write data. Drives, carriers and cold medium work together to achieve long-term data retention. A general reliability/availability model is presented to include hard errors, carrier presence, drive failures. Carrier aging is one of the key performance degrader in cold storage systems and needs to be appropriately modeled. Abstract: Cold data storage systems are used to allow long term digital preservation for institutions' archive. The common functionality among cold and warm/hot data storage is that the data is stored on some physical medium for read-back at a later time. However in cold storage, write and read operations are not necessarily done in the same exact geographical location. Hence, a third party assistance is typically utilized to bring together the medium and the drive. On the other hand, the reliability modeling of such a decomposed system poses few challenges that do not necessarily exist in other warm/hot storage alternatives such as fault detection and absence of the carrier, all totaling up to the data unavailability issues. In this paper, we propose a generalized non-homogenous Markov model that encompasses the aging of the carriers in order to address the requirements of today's cold data storage systems in which the data is encoded and spread across multiple nodes for the long-term data retention. We have derived useful lower/upper bounds on the overall system availability. Furthermore, the collected field data is used to estimate parameters of a Weibull distribution to accurately predict the lifetime of the carriers in an example scale-out setting.