@article {1502820,
	title = {TESLA: An Extended Study of an Energy-saving Agent that Leverages Schedule Flexibility },
	journal = {Journal of Autonomous Agents and Multiagent Systems, JAAMAS},
	volume = {28},
	number = {4},
	year = {2014},
	pages = {605-636},
	abstract = {This paper presents TESLA, an agent for optimizing energy usage in commercial buildings. TESLA{\textquoteright}s key insight is that adding flexibility to event/meeting
schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve
a stochastic mixed integer linear program (SMILP) for energy-efficient scheduling of
incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their
flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv)
surveys of real users which indicate that TESLA{\textquoteright}s assumptions of user flexibility hold
in practice. TESLA was evaluated on data gathered from over 110,000 meetings held
at nine campus buildings during an eight month period in 2011{\textendash}2012 at the University of Southern California (USC) and the Singapore Management University (SMU).
These results and analysis show that, compared to the current systems, TESLA can
substantially reduce overall energy consumption.},
	author = {Kwak, Jun-young and Varakantham, Pradeep and Maheswaran, Rajiv and Chang, Yu-Han and Tambe, Milind and Becerik-Gerber, Burcin and Wood, Wendy}
}
