Extending Demand Response to Tenants in Cloud Data Centers via Non-Intrusive Workload Flexibility Pricing

Participating in demand response programs is a promising tool for reducing energy costs in data centers by modulating energy consumption. Toward this end, data centers can employ a rich set of resource management knobs, such as workload shifting and dynamic server provisioning. Nonetheless, these knobs may not be readily available in a cloud data center (CDC) that serves cloud tenants/users, because workloads in CDCs are managed by tenants themselves who are typically charged based on a usage-based or flat-rate pricing and often have no incentive to cooperate with the CDC operator for demand response and cost saving. Toward breaking such “split incentive” hurdle, a few recent studies have tried market-based mechanisms, such as dynamic pricing, inside CDCs. However, such mechanisms often rely on complex designs that are hard to implement and difficult to cope with by tenants. To address this limitation, we propose a novel incentive mechanism that is not dynamic, i.e., it keeps pricing for cloud resources unchanged for a long period. While it charges tenants based on a usage-based pricing (UP) as used by today’s major cloud operators, it rewards tenants proportionally based on the time length that tenants set as deadlines for completing their workloads. This new mechanism is called UP with monetary reward (UPMR). We demonstrate the effectiveness of UPMR both analytically and empirically, showing: 1) UPMR can effectively reduce the CDC’s peak power consumption and energy cost without decreasing the CDC’s profit and 2) UPMR outperforms the state-of-the-art approaches that are used by today’s CDC operators to charge their tenants in terms of the profit gained by the CDC.

[1]  Shaolei Ren,et al.  Provably-Efficient Job Scheduling for Energy and Fairness in Geographically Distributed Data Centers , 2012, 2012 IEEE 32nd International Conference on Distributed Computing Systems.

[2]  S. Gupta,et al.  Thermal-aware task scheduling for data centers through minimizing heat recirculation , 2007, 2007 IEEE International Conference on Cluster Computing.

[3]  Mor Harchol-Balter,et al.  AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers , 2012, TOCS.

[4]  Jie Li,et al.  Modeling Demand Response Capability by Internet Data Centers Processing Batch Computing Jobs , 2015, IEEE Transactions on Smart Grid.

[5]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[6]  Hamed Mohsenian Rad,et al.  Propagating Electricity Bill onto Cloud Tenants: Using a Novel Pricing Mechanism , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[7]  Albert Y. Zomaya,et al.  A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems , 2010, Adv. Comput..

[8]  George Kesidis,et al.  On Fair Attribution of Costs under Peak-Based Pricing to Cloud Tenants , 2015, 2015 IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[9]  Shaolei Ren,et al.  Paying to save: Reducing cost of colocation data center via rewards , 2015, 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).

[10]  Adam Wierman,et al.  Opportunities and challenges for data center demand response , 2014, International Green Computing Conference.

[11]  Christos V. Verikoukis,et al.  A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms , 2015, IEEE Communications Surveys & Tutorials.

[12]  L H AndrewLachlan,et al.  Dynamic right-sizing for power-proportional data centers , 2013 .

[13]  Xiaowei Yang,et al.  CloudCmp: comparing public cloud providers , 2010, IMC '10.

[14]  George Kesidis,et al.  A Hierarchical Demand Response Framework for Data Center Power Cost Optimization under Real-World Electricity Pricing , 2014, 2014 IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems.

[15]  Albert G. Greenberg,et al.  The cost of a cloud: research problems in data center networks , 2008, CCRV.

[16]  Baochun Li,et al.  Reducing electricity demand charge for data centers with partial execution , 2013, e-Energy.

[17]  Thu D. Nguyen,et al.  Reducing electricity cost through virtual machine placement in high performance computing clouds , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[18]  Anand Sivasubramaniam,et al.  Energy storage in datacenters: what, where, and how much? , 2012, SIGMETRICS '12.

[19]  Z. Vale,et al.  Demand response in electrical energy supply: An optimal real time pricing approach , 2011 .

[20]  Hai Jin,et al.  When smart grid meets geo-distributed cloud: An auction approach to datacenter demand response , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[21]  Deep Medhi,et al.  Server Operational Cost Optimization for Cloud Computing Service Providers over a Time Horizon , 2011, Hot-ICE.

[22]  Amir-Hamed Mohsenian-Rad,et al.  Energy-Information Transmission Tradeoff in Green Cloud Computing , 2010 .

[23]  Anand Sivasubramaniam,et al.  Leveraging stored energy for handling power emergencies in aggressively provisioned datacenters , 2012, ASPLOS XVII.

[24]  Vincent W. S. Wong,et al.  Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid , 2010, IEEE Transactions on Smart Grid.

[25]  Yang Li,et al.  Towards dynamic pricing-based collaborative optimizations for green data centers , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[26]  Asuman E. Ozdaglar,et al.  Socially optimal pricing of cloud computing resources , 2011, VALUETOOLS.

[27]  A. Oudalov,et al.  Sizing and Optimal Operation of Battery Energy Storage System for Peak Shaving Application , 2007, 2007 IEEE Lausanne Power Tech.

[28]  Dean M. Tullsen,et al.  Battery Provisioning and Associated Costs for Data Center Power Capping , 2012 .

[29]  Thomas F. Wenisch,et al.  Power management of online data-intensive services , 2011, 2011 38th Annual International Symposium on Computer Architecture (ISCA).

[30]  Xue Liu,et al.  Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment , 2010, 2010 Proceedings IEEE INFOCOM.

[31]  George Kesidis,et al.  A Case for Virtualizing the Electric Utility in Cloud Data Centers , 2014, HotCloud.

[32]  Anand Sivasubramaniam,et al.  Optimal power cost management using stored energy in data centers , 2011, PERV.

[33]  Amir-Hamed Mohsenian-Rad,et al.  Coordination of Cloud Computing and Smart Power Grids , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[34]  Azer Bestavros,et al.  CloudPack - Exploiting Workload Flexibility through Rational Pricing , 2012, Middleware.

[35]  Wen-De Zhong,et al.  Demand Response in Data Centers Through Energy-Efficient Scheduling and Simple Incentivization , 2017, IEEE Systems Journal.

[36]  Ming Zhao,et al.  Profit Aware Load Balancing for Distributed Cloud Data Centers , 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.

[37]  Sangtae Ha,et al.  TUBE: time-dependent pricing for mobile data , 2012, SIGCOMM '12.

[38]  Rajkumar Buyya,et al.  SLA-Based Resource Allocation for Software as a Service Provider (SaaS) in Cloud Computing Environments , 2011, 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[39]  Lachlan L. H. Andrew,et al.  Greening Geographical Load Balancing , 2015, IEEE/ACM Transactions on Networking.

[40]  Navendu Jain,et al.  Managing cost, performance, and reliability tradeoffs for energy-aware server provisioning , 2011, 2011 Proceedings IEEE INFOCOM.

[41]  Adam Wierman,et al.  Data center demand response: avoiding the coincident peak via workload shifting and local generation , 2013, SIGMETRICS '13.

[42]  Hamed Mohsenian Rad,et al.  Energy and Performance Management of Green Data Centers: A Profit Maximization Approach , 2013, IEEE Transactions on Smart Grid.

[43]  Hamed Mohsenian Rad,et al.  Optimal integration of renewable energy resources in data centers with behind-the-meter renewable generator , 2012, 2012 IEEE International Conference on Communications (ICC).