Cambridge University Press / Computer-Communication Networks / Princeton University Press / Akamai / Google / YouTube / National Renewable Energy Laboratory / Microsoft / /
Country
Australia / United States / /
Currency
USD / pence / / /
Event
Reorganization / /
Facility
ICT Swinburne University of Technology / California Institute of Technology / /
IndustryTerm
constant electricity prices / lower energy costs / geographical load balancing systems / green energy / industrial electricity price / energy demands / electricity prices / Energy-efficient algorithms / distributed geographical load balancing algorithms / geographical load balancing algorithm / internet services / electricity costs / distributed algorithms / active/energy-saving states / energy coming / energy use / Internet connection / Internet data centers / renewable energy sources increases / distributed internet data centers / energy usage / energy / wasted brown energy / electricity price / electricity providers / fossil fuel energy / Internet Server Performance / energy consumption / electricity consumption / electricity cost / internet network distance / brown/green energy usage / energy consumers / sparse optimal solution / Internet-scale systems / distributed solution algorithm / energy pricing / wind-generated electricity / server energy / real-time systems / multi-electricity-market environment / cloud services / increased total energy usage / online / electricity price differences / slower algorithm / cheaper energy / dynamic server / brown energy / data center energy efficiency / energy price / energy price information / energy-efficient data centers / provable guarantees or ignore diverse network / static energy contracts / non-renewable energy / photovoltaic systems / given solution / renewable energy / server energy consumption / uses energy / processor sharing systems / demand-response and real-time markets / energy costs / large systems / replicated web servers / electricity / achievable energy cost / energy storage / geographical load balancing solutions / local electricity price / energy cost / active server / large Internet service / green energy usage / renewable energy electricity policies / gradient projection algorithm / brown energy consumption / web clients / peak average wind energy / solar energy / brown energy use / Internet-scale system / brown energy usage / web services / /
NaturalFeature
West Coast East Coast / /
Organization
Cambridge University / U.S. Environmental Protection Agency / Princeton University / IMC / Lachlan L. H. Andrew Faculty / Swinburne University of Technology / Lee Center for Advanced Networking / California Institute of Technology / National Science Foundation / Congress / ARC / US Census Bureau / /
Person
R. Das / C. Lefurgy / Adam Wierman / O. Bilgir / A. Gandhi / Minghong Lin / M. Harchol-Balter / K. Le / R. Bianchini / T. D. Nguyen / M. Martonosi / Steven H. Low / /
Position
General / Governor / model for data center costs focuses / /
ProgrammingLanguage
DC / /
ProvinceOrState
Virginia / Washington / South Carolina / California / Georgia / Texas / Illinois / Oregon / Florida / North Carolina / /
Greening Geographical Load Balancing Zhenhua Liu, Minghong Lin, Adam Wierman, Steven H. Low CMS, California Institute of Technology, Pasadena {zliu2,mhlin,adamw,slow}@caltech.edu