Title: Modeling Impact of Human Errors on the Data Unavailability and Data Loss of Storage Systems,
Abstract: Data storage systems and their availability play a crucial role in
contemporary datacenters. Despite using mechanisms such as automatic fail-over
in datacenters, the role of human agents and consequently their destructive
errors is inevitable. Due to very large number of disk drives used in exascale
datacenters and their high failure rates, the disk subsystem in storage systems
has become a major source of Data Unavailability (DU) and Data Loss (DL)
initiated by human errors. In this paper, we investigate the effect of
Incorrect Disk Replacement Service (IDRS) on the availability and reliability
of data storage systems. To this end, we analyze the consequences of IDRS in a
disk array, and conduct Monte Carlo simulations to evaluate DU and DL during
mission time. The proposed modeling framework can cope with a) different
storage array configurations and b) Data Object Survivability (DOS),
representing the effect of system level redundancies such as remote backups and
mirrors. In the proposed framework, the model parameters are obtained from
industrial and scientific reports alongside field data which have been
extracted from a datacenter operating with 70 storage racks. The results show
that ignoring the impact of IDRS leads to unavailability underestimation by up
to three orders of magnitude. Moreover, our study suggests that by considering
the effect of human errors, the conventional beliefs about the dependability of
different Redundant Array of Independent Disks (RAID) mechanisms should be
revised. The results show that RAID1 can result in lower availability compared
to RAID5 in the presence of human errors. The results also show that employing
automatic fail-over policy (using hot spare disks) can reduce the drastic
impacts of human errors by two orders of magnitude.