@PhdThesis{riedel:thesis,
  author = {Erik Riedel},
  title = {Active Disks - Remote Execution for Network-Attached Storage},
  year = {1999},
  month = {November},
  school = {Carnegie Mellon University},
  address = {Pittsburgh, PA},
  URL = {http://www.pdl.cs.cmu.edu/ftp/Active/riedel_thesis_abs.html},
  keywords = {storage, active disks, embedded systems, architecture, databases,
  data mining, disk scheduling, pario-bib},
  abstract = {Today's commodity disk drives, the basic unit of storage for
  computer systems large and small, are actually small computers, with a
  processor, memory, and 'network' connection, along with the spinning magnetic
  material that permanently stores the data. As more and more of the
  information in the world becomes digitally available, and more and more of
  our daily activities are recorded and stored, people are increasingly finding
  value in analyzing, rather than simply storing and forgetting, these large
  masses of data. Sadly, advances in I/O performance have lagged the
  development of commodity processor and memory technology, putting pressure on
  systems to deliver data fast enough for these types of data-intensive
  analysis. This dissertation proposes a system called Active Disks that takes
  advantage of the processing power on individual disk drives to run
  application-level code. Moving portions of an application's processing
  directly to the disk drives can dramatically reduce data traffic and take
  advantage of the parallelism already present in large storage systems. It
  provides a new point of leverage to overcome the I/O bottleneck. \par This
  dissertation presents the factors that will make Active Disks a reality in
  the not-so-distant future, the characteristics of applications that will
  benefit from this technology, an analysis of the improved performance and
  efficiency of systems built around Active Disks, and a discussion of some of
  the optimizations that are possible with more knowledge available directly at
  the devices. It also compares this work with previous work on database
  machines and examines the opportunities that allow us to take advantage of
  these promises today where previous approaches have not succeeded. The
  analysis is motivated by a set of applications from data mining, multimedia,
  and databases and is performed in the context of a prototype Active Disk
  system that shows dramatic speedups over a system with traditional, "dumb"
  disks.}
}