Data Mining for Information Storage Reliability Assessment by Relative Values

Abstract

The data ambiguity problem for heterogeneous sets of equipment reliability indicators is considered. In fact, the same manufacturers do not always unambiguously fill the SMART parameters with the corresponding values for their different models of hard disk drives. In addition, some of the parameters are sometimes empty, while the other parameters have only zero values.The scientific task of the research consists in the need to define such a set of parameters that will allow us to obtain a comparative assessment of the reliability of each individual storage device of any model of any manufacturer for its timely replacement.The following conditions were used to select the parameters suitable for evaluating their relative values:1) The parameter values for normally operating drives should always be greater or lower than for the failed ones;2) The monotonicity of changes in the values of parameters in the series should be observed: normally working, withdrawn prematurely, failed;3) The first two conditions must be fulfilled both in general and in particular, for example, for the drives of each brand separately.Separate averaging of the values for normally operating, early decommissioned and failed storage media was performed. The maximum of these three values was taken as 100%. The relative distribution of values for each parameter was studied.Five parameters were selected (5 – “Reallocated sectors count”, 7 – “Seek error rate”, 184 – “End-to-end error”, 196 – “Reallocation event count”, 197 – “Current pending sector count”, plus another four (1 – “Raw read error rate”, 10 – “Spin-up retry counts”, 187 – “Reported uncorrectable errors”, 198 – “Uncorrectable sector counts”), which require more careful analysis, and one (194 – “Hard disk assembly temperature”) for prospective use in solid-state drives, as a result of the relative value study of their suitability for use upon evaluating the reliability of data storage devices.

Study of Failure Hazard Degree in Large Data Centers

“…A proof of the priority of the number of reassigned sectors when assessing the state of a hard disk is presented in [4], which shows the results of a study on 100,000 drives in servers around the world, performed by Google. Additional parameters can be selected in two different ways: relative [5] and absolute values [6]. A similar approach allows you to: 1) Track drives in which the current value is close to the limit level; 2) Keep control of drives that slowly but steadily collapse;…”