NDLI: A truthful incentive mechanism for emergency demand response in colocation data centers

Content Provider	IEEE Xplore Digital Library
Author	Linquan Zhang Shaolei Ren Chuan Wu Zongpeng Li
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada (Linquan Zhang; Zongpeng Li) \|\| Sch. of Comput. & Inf. Sci., Florida Int. Univ., Miami, FL, USA (Shaolei Ren) \|\| Dept. of Comput. Sci., Univ. of Hong Kong, Hong Kong, China (Chuan Wu)
Abstract	Data centers are key participants in demand response programs, including emergency demand response (EDR), where the grid coordinates large electricity consumers for demand reduction in emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers, this work studies EDR in multi-tenant colocation data centers where servers are owned and managed by individual tenants. EDR in colocation data centers is significantly more challenging, due to lack of incentives to reduce energy consumption by tenants who control their servers and are typically on fixed power contracts with the colocation operator. Consequently, to achieve demand reduction goals set by the EDR program, the operator has to rely on the highly expensive and/or environmentally-unfriendly on-site energy backup/generation. To reduce cost and environmental impact, an efficient incentive mechanism is therefore in need, motivating tenants' voluntary energy reduction in case of EDR. This work proposes a novel incentive mechanism, Truth-DR, which leverages a reverse auction to provide monetary remuneration to tenants according to their agreed energy reduction. Truth-DR is computationally efficient, truthful, and achieves 2-approximation in colocation-wide social cost. Trace-driven simulations verify the efficacy of the proposed auction mechanism.
Starting Page	2632
Ending Page	2640
File Size	380179
Page Count	9
File Format	PDF
ISBN	9781479983810
DOI	10.1109/INFOCOM.2015.7218654
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load management Servers Power grids Power demand Energy consumption Algorithm design and analysis Approximation algorithms
Content Type	Text
Resource Type	Article

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