FYI...
Hello Lee,
sounds interesting. The agenda for today is to agree on the
work packages on which we will focus on in the specification document.
So I think this will consume most of the time in the
session.
I propose that we have a follow-up on this in the
next call discussing your proposal
explicitly.
Let me give you a quick answer to your
proposal:
One requirement of the interface(s) the working group
is looking into is dealing with policies (such as proposed below). In
the course of this work package I think we can explore this topic.
However, I do not think it is the main scope of this working group
to define / specify the architecture & algorithm to enforce this
policy. Additionally, the interaction among a virtualization manager and the
sensors to measure power consumption metrics is, I think, also not scope.
Basically, policy enforcement is a platform specific detail that is
hidden by the management layer and thus not explicitly exposed.
However, we can have a detailed discussion in a
dedicated concall.
Regards, Erol
Erol, et al.,
I will be attending tomorrow's telecon and would like to see if there
is any interest in pursuing a project along the lines of what's
proposed
below. This is part of an effort to use "targeted projects" as a
way
to produce "value" for members. I've attached a short slide
deck
that describes the overall process and how it might work. It
also
occurs to me that perhaps we can get the RESERVOIR project
interested. Kate Keahey from Argonne is already interested.
Let's talk tomorrow, if we can fit this into the agenda...
Best regards,
--Craig
==================================================
Project
Proposal: Using Virtual Machines to Enact Energy
Policy
Goal:
The goal of this proposed project is to study and
demonstrate the
realization and enforcement of energy policy, i.e., Green IT,
through
the initial placement and migration of virtual machines
(VMs).
Why it it important:
The management of energy utilization
has rapidly become a
critical issue for industry, government, and academia,
since
many computing installations are exceeding the available
electrical
supply, cooling and floor space. The use of VMs
to dynamically manage
workload location and distribution
is considered to be a highly promising
method for managing
energy efficiency and meeting corporate
requirements.
To Whom This is Important:
This project would
benefit all members that are concerned about
maximizing the
cost-effectiveness and efficiency of data center
operation. Since this
approach is inherently distributed, it may
incorporate and rely upon many
traditional grid computing concepts.
Technical
Description:
Managing energy efficiency to achieve an energy policy would
be a
matter of:
(1) Integration of appropriate monitoring capabilities
to monitor
current energy consumption at a given site,
e.g., cooling,
processors, storage, etc.,
(2) The
definition of semantically complete and consistent
representations of energy policy, possibly using XML,
(3) The use of (a)
policy representations and (b) current (monitored)
system
state, to direct (c) VM placement and migration to achieve
and enforce energy policy. This may be done
through a set of
energy management peers that monitor the
energy usage at their own
site, gossip among themselves
about how workload should be
distributed, and act
accordingly.
This project could possibly leverage capabilities already
developed by
personnel at Argonne National Laboratory (ANL). ANL has
worked on the
concept of virtual workspaces and virtual clusters where sets
of VMs
are managed together and yet may be distributed across remote
physical
resources. This is very attractive since exploiting existing
capabilities
always makes it easier to quickly demonstrate new
capabilities.
Required Resources:
This project would require at
least two sites where VMs could be
dynamically managed. More sites
would be preferable, but not to the
point where it becomes unmanageable for a
targeted demonstration. A
user workload would have to be generated,
either synthetically or
through the use of real applications, that would
provide VMs that need
to be allocated. Personnel would have to be
available and supported to:
1) Build and integrate (or possibly simulate)
the monitoring subsystem,
2) Devise an energy policy
representation,
3) Build the p2p control subsystem that would use the
monitored
information and the energy policy to determine VM
initial placement
and migration, and
4) perform
experiments to verify the effectiveness of this approach of
enforcing energy policy.
Time Frame:
It is expected that with the
right provisioning, this project could be
completed within six months.
Each of the subtask identified above
could be done is the simplest manner possible to demonstrate a
proof of
concept implementation that leverages existing capabilities
for VM placement, etc.