Foundations of queueing theory
Foundations of queueing theory
Optimal power allocation in server farms
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
INFOCOM'10 Proceedings of the 29th conference on Information communications
Capping the brown energy consumption of Internet services at low cost
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Stochastic Network Optimization with Application to Communication and Queueing Systems
Stochastic Network Optimization with Application to Communication and Queueing Systems
Optimal power cost management using stored energy in data centers
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Greening geographical load balancing
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
Online job-migration for reducing the electricity bill in the cloud
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
Leveraging stored energy for handling power emergencies in aggressively provisioned datacenters
ASPLOS XVII Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
Renewable and cooling aware workload management for sustainable data centers
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Energy storage in datacenters: what, where, and how much?
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Provably-Efficient Job Scheduling for Energy and Fairness in Geographically Distributed Data Centers
ICDCS '12 Proceedings of the 2012 IEEE 32nd International Conference on Distributed Computing Systems
Proceedings of the 9th international conference on Autonomic computing
Carbon-Aware Energy Capacity Planning for Datacenters
MASCOTS '12 Proceedings of the 2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers
ACM Transactions on Computer Systems (TOCS)
Electricity Bill Capping for Cloud-Scale Data Centers that Impact the Power Markets
ICPP '12 Proceedings of the 2012 41st International Conference on Parallel Processing
Data center demand response: avoiding the coincident peak via workload shifting and local generation
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
| Hi-index | 0.00 |
Due to the huge electricity consumption and carbon emissions, data center operators have been increasingly pressured to reduce their net carbon footprints to zero, i.e., carbon neutrality. In this paper, we propose an efficient online algorithm, called CNDC (optimization for Carbon-Neutral Data Center), to control the number of active servers for minimizing the data center operational cost (defined as a weighted sum of electricity cost and delay cost) while satisfying carbon neutrality without requiring long-term future information. Unlike prior research on carbon neutrality, we explore demand-responsive electricity price enabled by the emerging smart grid technology and demonstrate that it can be incorporated in data center operation to reduce the operational cost. Leveraging the Lyapunov optimization technique, we prove that CNDC achieves a close-to-minimum operational cost compared to the optimal algorithm with future information, while bounding the potential violation of carbon neutrality, in an almost arbitrarily random environment. We also perform trace-based simulation as well as experiment studies to complement the analysis. The results show that CNDC reduces the cost by more than 20% (compared to state-of-the-art prediction-based algorithm) while resulting in a smaller carbon footprint. Moreover, by incorporating demand-response electricity prices, CNDC can further decrease the average cost by approximately 2.5%, translating into hundreds of thousands of dollars per year.