@Article{alvarez:jminerva,
  author = {Guillermo A. Alvarez and Elizabeth Borowsky and Susie Go and
  Theodore H. Romer and Ralph Becker-Szendy and Richard Golding and Arif
  Merchant and Mirjana Spasojevic and Alistair Veitch and John Wilkes},
  title = {Minerva: An automated resource provisioning tool for large-scale
  storage systems},
  journal = {ACM Transactions on Computer Systems},
  year = {2001},
  month = {November},
  volume = {19},
  number = {4},
  pages = {483--518},
  URL = {http://doi.acm.org/10.1145/502912.502915},
  keywords = {disk array, storage system, RAID, automatic design, parallel I/O,
  pario-bib},
  abstract = {Enterprise-scale storage systems, which can contain hundreds of
  host computers and storage devices and up to tens of thousands of disks and
  logical volumes, are difficult to design. The volume of choices that need to
  be made is massive, and many choices have unforeseen interactions. Storage
  system design is tedious and complicated to do by hand, usually leading to
  solutions that are grossly over-provisioned, substantially under-performing
  or, in the worst case, both.To solve the configuration nightmare, we present
  minerva: a suite of tools for designing storage systems automatically.
  Minerva uses declarative specifications of application requirements and
  device capabilities; constraint-based formulations of the various
  sub-problems; and optimization techniques to explore the search space of
  possible solutions.This paper also explores and evaluates the design
  decisions that went into Minerva, using specialized micro- and
  macro-benchmarks. We show that Minerva can successfully handle a workload
  with substantial complexity (a decision-support database benchmark). Minerva
  created a 16-disk design in only a few minutes that achieved the same
  performance as a 30-disk system manually designed by human experts. Of equal
  importance, Minerva was able to predict the resulting system's performance
  before it was built.}
}