402x Filetype PPTX File size 0.86 MB Source: www.cs.ucf.edu
Contents
Energy use and ecological impact of data centers
Service Level Agreements
Software licensing
Basic architecture of cloud platforms
Open-source platforms for cloud computing
Eucalyptus
Nebula
Nimbus
Cloud applications
Challenges
Existing and new applications
Coordination and the Zookeeper
The Map-Reduce programming model
The GrepTheWeb application
Clouds in science and engineering
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The ratio of the costs for medium size (with around 1,000
systems) versus large (with more than 50,000 systems) data
centers.
The costs for the computing and communication infrastructure for
medium and large data centers:
(a) networking - in dollars per Mbit/sec/month;
(b) storage - dollars per GByte/month; and
(c) system administrators.
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AWS – Amazon Web Services
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Energy use; ecological impact of data centers
A 2010 report shows that a typical Google cluster spends most of its time
within the 10-50% CPU utilization range.
The operating efficiency of a system is captured by performance per Watt
of power. Imbalance between the rates, for example, during the period
1998-2007, the performance of supercomputers has increased 7000%
while their operating efficiency has increased only 2000%!!
In an ideal world, the energy consumed by an idle system should be near
zero and should grow linearly with the system load. In real life, even
machines whose power requirements scale linearly when idle use more
than half the power they use at full load.
An energy-proportional system consumes no power when idle, very little
power under a light load and, gradually, more power as the load
increases. By definition, an ideal energy-proportional system is always
operating at 100% efficiency. Humans are a good approximation of an
ideal energy proportional system; the human energy consumption is
about 70 W at rest, 120 W on average on a daily basis, and can go as
high as 1000 - 2000 W during a strenuous, short time effort.
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