[Colloquium] Sotomayor/Dissertation Defense/Jul 7, 2010

[Margaret Jaffey]

       Department of Computer Science/The University of Chicago

                     *** Dissertation Defense ***


Candidate:  Borja Sotomayor

Date:  Wednesday, July 7, 2010

Time:  10:00 AM

Place:  Searle 240A (5735 Ellis)

Title: Provisioning Computational Resources Using Virtual Machines and
Leases

Abstract:
The need for computational resources has, over the years, become a
fundamental requirement in both science and industry. In many cases,
this need is transient: a user may only require computational
resources for the duration of a well-defined task. For example, a
scientist could require a large number of computers to run a
simulation for just a few hours, but might not need those computers at
any specific time (as long as they are made available in a reasonable
amount of time). A college instructor may want to make a cluster of
computers available to students during the course's lab sessions, at
very specific times during the week, and with a specific software
configuration. A telecommunications company could posses an existing
infrastructure that hosts a number of websites, but may need to
supplement that infrastructure with additional resources during
periods of unforeseen increased web traffic, meaning those resources
have to made available right away with very little advance notice.

These transient resource usage scenarios pose the problem of how to
provision shared computational resources efficiently. This problem has
been studied for decades, resulting in approaches that tend to be
highly specialized to specific usage scenarios. For example, the
problem of how to run multiple jobs on a shared cluster has been
extensively studied, resulting in job management systems systems like
Torque/Maui, Sun Grid Engine, LoadLeveler, and many others, that can
queue and prioritize job requests efficiently (in these systems,
efficiency is defined in terms of a variety of metrics, including
waiting times and resource utilization). Such a system would meet the
requirements of the scientist wanting to run simulations during a few
hours but, on the other hand, the college instructor and the
telecommunications company mentioned above would be ill-served by a
job management system and the efficiency metrics typically used in job
management. Conversely, other resource provisioning approaches are not
particularly well suited for job-oriented computations (this point
will be explored in greater detail throughout this chapter).

Thus, there is no general solution that can provision resources
meeting the requirements of different usage scenarios simultaneously,
such as those mentioned above, reconciling the different measures of
efficiency in each scenario. More specifically, much of my work is
motivated by the combination of best-effort resource requirements,
where a user needs computational resources but is willing to wait for
them (possibly setting a deadline), and advance reservation resource
requirements, where the resources must be available at a specific
time. In the former, efficiency is typically measured in terms of
waiting times (or similar metrics such as turnaround times or
slowdowns) or throughput, while the latter is usually concerned with
providing the requested resources at exactly the agreed-upon times
without interruption, and both are concerned with maximizing the use
of hardware resources and possibly monetary profit. Although both
best-effort and advance reservation provisioning have been studied
separately, the combination of both is known to produce utilization
problems and is discouraged in practice.

In this dissertation I seek to develop a resource provisioning model
and architecture that can support multiple resource provisioning
scenarios efficiently and simultaneously, with an initial focus on the
best-effort and advance-reservation cases mentioned above, and arguing
in favour of a lease-based model, where leases are implemented as
virtual machines (VMs). The main contribution of this dissertation
are:

1. A resource provisioning model and architecture that uses leases as
a fundamental abstraction and virtual machines as an implementation
vehicle.

2. Lease scheduling algorithms that mitigate the utilization problems
typically encountered when scheduling advance reservations.

3. A model for the various overheads involved in using virtual
machines, and algorithms that (a) allow lease terms to be met even in
the presence of this overhead, and (b) mitigate this overhead in some
cases.

4. Price-based policies for lease admission, showing that an adaptive
pricing strategy can, in some cases, generate more revenue than other
baseline pricing strategies, but does so by using fewer resources,
thus giving resource providers more excess capacity that can
potentially be sold to other users.

As a technological contribution, I also present Haizea
(http://haizea.cs.uchicago.edu/), an open source reference
implementation of the architecture and algorithms described in this
dissertation.

Borja's advisor is Prof. Ian Foster

Login to the Computer Science Department website for details,
including a draft copy of the dissertation:

 https://www.cs.uchicago.edu/phd/phd_announcements#borja

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Margaret P. Jaffey            margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 156)               (773) 702-6011
The University of Chicago      http://www.cs.uchicago.edu
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