@techreport{TD:100040,
	att_abstract={{Information and communications technology accounts for
a significant fraction of worldwide electricity consumption.
Given the relentless growth of demand for communications
services, telecommunications providers will need to transition
to more energy-efficient technology in order to limit
their environmental impact. Here we focus on priority-setting
for the transition process. In particular, we introduce a
method for statistically inferring the electricity consumption
of different components of the installed base of telecommunications
equipment, while avoiding the high cost of performing
direct measurements. Our method relies only on
databases of installed equipment in central offices, together
with aggregate electricity consumption per office. It takes
advantage of inter-office variation in installed equipment to
partition per-office electricity consumption by major equipment
type. When applied to a collection of 3,918 central
offices of a major U.S. telecommunications provider, our approach
reveals the (previously unknown) network-wide energy
consumption of each major type of equipment. In particular,
we find that electricity consumption is dominated by
Class-5 telephone switches, which account for 43% of aggregate
consumption, and which should therefore be a primary
target of central office electricity conservation efforts.}},
	att_authors={sp8212, sw1213, mf2182, pm1519},
	att_categories={},
	att_copyright={{ACM}},
	att_copyright_notice={{(c) ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution.
The definitive version was published in ACM GreenMetrics Workshop {{, Volume 38}}{{, Issue 3}}{{, 2010-10-10}}.}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100040},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100040_DS1_2010-05-04T16:41:40.331Z.pdf},
	author={Steven Phillips and Sheryl Woodward and Mark Feuer and Peter Magill},
	institution={{ACM SIGMETRICS Performance Evaluation Review}},
	month={October},
	title={{A regression approach to infer electricity consumption of legacy telecom equipment}},
	year=2010,
}