An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Statistical profiling-based techniques for effective power provisioning in data centers
Proceedings of the 4th ACM European conference on Computer systems
Batch Job Profiling and Adaptive Profile Enforcement for Virtualized Environments
PDP '09 Proceedings of the 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing
Cutting the electric bill for internet-scale systems
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
INFOCOM'10 Proceedings of the 29th conference on Information communications
DONAR: decentralized server selection for cloud services
Proceedings of the ACM SIGCOMM 2010 conference
Server workload analysis for power minimization using consolidation
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
Power Consumption Prediction and Power-Aware Packing in Consolidated Environments
IEEE Transactions on Computers
Capping the brown energy consumption of Internet services at low cost
GREENCOMP '10 Proceedings of the International Conference on Green Computing
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
Power management of online data-intensive services
Proceedings of the 38th annual international symposium on Computer architecture
OptiTuner: On Performance Composition and Server Farm Energy Minimization Application
IEEE Transactions on Parallel and Distributed Systems
Geographical load balancing with renewables
ACM SIGMETRICS Performance Evaluation Review
GreenHadoop: leveraging green energy in data-processing frameworks
Proceedings of the 7th ACM european conference on Computer Systems
Minimizing data center SLA violations and power consumption via hybrid resource provisioning
IGCC '11 Proceedings of the 2011 International Green Computing Conference and Workshops
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
BigHouse: A simulation infrastructure for data center systems
ISPASS '12 Proceedings of the 2012 IEEE International Symposium on Performance Analysis of Systems & Software
Interactive analytical processing in big data systems: a cross-industry study of MapReduce workloads
Proceedings of the VLDB Endowment
Proceedings of the 9th international conference on Autonomic computing
Dynamic energy-aware capacity provisioning for cloud computing environments
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
Online algorithms for geographical load balancing
IGCC '12 Proceedings of the 2012 International Green Computing Conference (IGCC)
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Demand response is a crucial aspect of the future smart grid. It has the potential to provide significant peak demand reduction and to ease the incorporation of renewable energy into the grid. Data centers' participation in demand response is becoming increasingly important given their high and increasing energy consumption and their flexibility in demand management compared to conventional industrial facilities. In this paper, we study two demand response schemes to reduce a data center's peak loads and energy expenditure: workload shifting and the use of local power generation. We conduct a detailed characterization study of coincident peak data over two decades from Fort Collins Utilities, Colorado and then develop two algorithms for data centers by combining workload scheduling and local power generation to avoid the coincident peak and reduce the energy expenditure. The first algorithm optimizes the expected cost and the second one provides a good worst-case guarantee for any coincident peak pattern, workload demand and renewable generation prediction error distributions. We evaluate these algorithms via numerical simulations based on real world traces from production systems. The results show that using workload shifting in combination with local generation can provide significant cost savings (up to 40% under the Fort Collins Utilities charging scheme) compared to either alone.