TY - GEN
T1 - Carbon-aware Load Balancing for Geo-distributed Cloud Services
AU - Zhou, Zhi
AU - Liu, Fangming
AU - Xu, Yong
AU - Zou, Ruolan
AU - Xu, Hong
AU - Lui, John C.S.
AU - Jin, Hai
PY - 2013/8
Y1 - 2013/8
N2 - Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.
AB - Recently, datacenter carbon emission has become an emerging concern for the cloud service providers. Previous works are limited on cutting down the power consumption ofthe datacenters to defuse such a concern. In this paper, we show how the spatial and temporal variabilities of the electricity carbon footprint can be fully exploited to further green the cloud running on top of geographically distributed datacenters. We jointly consider the electricity cost, service level agreement (SLA) requirement, and emission reduction budget. To navigate such a three-way tradeoff, we take advantage of Lyapunov optimization techniques to design and analyze a carbon-aware control framework, which makes online decisions on geographical load balancing, capacity right-sizing, and server speed scaling. Results from rigorous mathematical analyses and real-world trace-driven empirical evaluation demonstrate its effectiveness in both minimizing electricity cost and reducing carbon emission.
UR - http://www.scopus.com/inward/record.url?scp=84894559511&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84894559511&origin=recordpage
U2 - 10.1109/MASCOTS.2013.31
DO - 10.1109/MASCOTS.2013.31
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9780769551029
SP - 232
EP - 241
BT - Proceedings - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication, MASCOTS 2013
T2 - 2013 IEEE 21st International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2013)
Y2 - 14 August 2013 through 16 August 2013
ER -
