Data backup policies with failure-oblivious computing in reliability theory

Xu-Feng Zhao, Dong Wang (), Satoshi Mizutani and Toshio Nakagawa
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Xu-Feng Zhao: Nanjing University of Aeronautics and Astronautics
Dong Wang: Nanjing University of Aeronautics and Astronautics
Satoshi Mizutani: Aichi Institute of Technology
Toshio Nakagawa: Aichi Institute of Technology

Annals of Operations Research, 2025, vol. 348, issue 1, No 7, 117-146

Abstract: Abstract In-memory database systems are becoming an efficient technology to achieve the goal of high throughput rate and low latency time, however, they are more vulnerable than disk-based database systems due to the feature of their running carriers, so that it becomes a critical problem to design data backup and recovery policies to prevent memory failures for in-memory database management systems. From this viewpoint, this paper firstly describes the stochastic processes of bulk-data update, triggers of failure-oblivious computing and in-memory database failure, and then model the expected cost rates for data backup and recovery when full backups are implemented at time T and at bulk-data update N, respectively. In order to compare the policies of T and N, integrated models of the backup policies implemented at time T and at bulk-data update N are studied, using the triggering approaches of first and last in maintenance theory. Furthermore, the policies of T and N are reconsidered when full backup is planned at the completion of the forthcoming bulk-data update. In addition, a cumulative cost of failure-oblivious computing is considered in the modified backup policies. All of the expected cost rates and their optimum policies of full backups are obtained in analytical ways.

Keywords: Bulk-data; Incremental backup; In-memory database; Memory error; Reliability theory (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-022-04941-8

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