@techreport{TD:100737,
	att_abstract={{Modern day enterprises have a large IT infrastructure
comprising thousands of applications running on
servers housed in tens of data centers geographically spread
out. These enterprises periodically perform a transformation of
their entire IT infrastructure to simplify, decrease operational
costs and enable easier management. However, the large
number of different kinds of applications and data centers
involved and the variety of constraints make the task of
data center transformation challenging. The state-of-the-art
technique for performing this transformation is simplistic, often
unable to account for all but the simplest of constraints. We
present eTransform, a system for generating a transformation
and consolidation plan for the IT infrastructure of large
scale enterprises. We devise a linear programming based
approach that simultaneously optimizes all the costs involved
in enterprise data centers taking into account the constraints
of applications groups. Our algorithm handles the various
idiosyncrasies of enterprise data centers like volume discounts
in pricing, wide-area network costs, traffic matrices, latency
constraints, distribution of users accessing the data etc. We
include a disaster recovery (DR) plan, so that eTransform, thus
provides an integrated disaster recovery and consolidation plan
to transform the enterprise IT infrastructure.
We use eTransform to perform case studies based on real
data from three different large scale enterprises. In our
experiments, eTransform is able to suggest a plan to reduce the
operational costs by more than 50% from the �as-is� state of
these enterprise to the consolidated enterprise IT environment.
Even including the DR capability, eTransform is still able to
reduce the operational costs by more than 25% from the
simple �as-is� state. In our experiments, eTransform is able to
simultaneously optimize multiple parameters and constraints
and discover solutions that are 7x cheaper than other solutions.}},
	att_authors={kr2812},
	att_categories={},
	att_copyright={{IEEE}},
	att_copyright_notice={{}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100737},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100737_DS1_2011-12-04T17:40:08.963Z.pdf},
	author={Kadangode Ramakrishnan and Rahul Singh, University of Massachusetts, Amherst and Prashant Shenoy, University of Massachusetts, Amherst and Rahul Kelkar, Tata Research Development and Design Center, Pune and Harrick Vin},
	institution={{IEEE International Conference on Distributed Computing Systems (ICDCS)}},
	month={June},
	title={{eTransform: Transforming Enterprise Data Centers by Automated Consolidation}},
	year=2012,
}