A market approach for handling power emergencies in multi-tenant data center

Power oversubscription in data centers may occasionally trigger an emergency when the aggregate power demand exceeds the capacity. Handling such an emergency requires a graceful power capping solution that minimizes the performance loss. In this paper, we study power capping in a multi-tenant data center where the operator supplies power to multiple tenants that manage their own servers. Unlike owner-operated data centers, the operator lacks control over tenants' servers. To address this challenge, we propose a novel market mechanism based on supply function bidding, called COOP, to financially incentivize and coordinate tenants' power reduction for minimizing total performance loss (quantified in performance cost) while satisfying multiple power capping constraints. We build a prototype to show that COOP is efficient in terms of minimizing the total performance cost, even compared to the ideal but infeasible case that assumes the operator has full control over tenants' servers. We also demonstrate that COOP is "win-win", increasing the operator's profit (through oversubscription) and reducing tenants' cost (through financial compensation for their power reduction during emergencies).

[1]  Alan Jay Smith,et al.  PACE: a new approach to dynamic voltage scaling , 2004, IEEE Transactions on Computers.

[2]  Benjamin C. Lee,et al.  Navigating heterogeneous processors with market mechanisms , 2013, 2013 IEEE 19th International Symposium on High Performance Computer Architecture (HPCA).

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

[4]  Lachlan L. H. Andrew,et al.  Dynamic Right-Sizing for Power-Proportional Data Centers , 2011, IEEE/ACM Transactions on Networking.

[5]  Luiz André Barroso,et al.  The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines , 2009, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines.

[6]  Thu D. Nguyen,et al.  ApproxHadoop: Bringing Approximations to MapReduce Frameworks , 2015, ASPLOS.

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

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

[9]  Benjamin Hindman,et al.  Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.

[10]  S. Low,et al.  Demand Response With Capacity Constrained Supply Function Bidding , 2016 .

[11]  Qi Li,et al.  Thermal time shifting: Leveraging phase change materials to reduce cooling costs in warehouse-scale computers , 2015, 2015 ACM/IEEE 42nd Annual International Symposium on Computer Architecture (ISCA).

[12]  Jie Liu,et al.  No more electrical infrastructure: towards fuel cell powered data centers , 2014, OPSR.

[13]  Anand Sivasubramaniam,et al.  Virtualizing power distribution in datacenters , 2013, ISCA.

[14]  Adam Wierman,et al.  Pricing data center demand response , 2014, SIGMETRICS '14.

[15]  Houman Homayoun,et al.  Managing distributed UPS energy for effective power capping in data centers , 2012, 2012 39th Annual International Symposium on Computer Architecture (ISCA).

[16]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .

[17]  Wolf-Dietrich Weber,et al.  Power provisioning for a warehouse-sized computer , 2007, ISCA '07.

[18]  John N. Tsitsiklis,et al.  Parameterized Supply Function Bidding: Equilibrium and Efficiency , 2011, Oper. Res..

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

[20]  Xiaorui Wang,et al.  How much power oversubscription is safe and allowed in data centers , 2011, ICAC '11.

[21]  Sriram Sankar,et al.  CoolProvision: underprovisioning datacenter cooling , 2015, SoCC.

[22]  Xiaorui Wang,et al.  Data Center Sprinting: Enabling Computational Sprinting at the Data Center Level , 2015, 2015 IEEE 35th International Conference on Distributed Computing Systems.

[23]  George Kesidis,et al.  Recouping Energy Costs From Cloud Tenants: Tenant Demand Response Aware Pricing Design , 2015, e-Energy.

[24]  Adam Wierman,et al.  Greening Multi-Tenant Data Center Demand Response , 2015, PERV.

[25]  Kathleen Gillogly,et al.  Environmental Sustainability Policy in Thailand: Global Systems, Thai Localism , 2014 .

[26]  Shaolei Ren,et al.  A truthful incentive mechanism for emergency demand response in colocation data centers , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[27]  Christoforos E. Kozyrakis,et al.  Towards energy proportionality for large-scale latency-critical workloads , 2014, 2014 ACM/IEEE 41st International Symposium on Computer Architecture (ISCA).

[28]  Srinivasan Keshav,et al.  It's not easy being green , 2012, CCRV.

[29]  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).

[30]  Nanning Zheng,et al.  HEB: Deploying and managing hybrid energy buffers for improving datacenter efficiency and economy , 2015, 2015 ACM/IEEE 42nd Annual International Symposium on Computer Architecture (ISCA).

[31]  Jie Liu,et al.  Underprovisioning backup power infrastructure for datacenters , 2014, ASPLOS.

[32]  Benjamin C. Lee,et al.  REF: resource elasticity fairness with sharing incentives for multiprocessors , 2014, ASPLOS.

[33]  Jie Liu,et al.  Power Budgeting for Virtualized Data Centers , 2011, USENIX Annual Technical Conference.

[34]  Xiaorui Wang,et al.  SHIP: Scalable Hierarchical Power Control for Large-Scale Data Centers , 2009, 2009 18th International Conference on Parallel Architectures and Compilation Techniques.

[35]  Kushagra Vaid,et al.  ACE: abstracting, characterizing and exploiting peaks and valleys in datacenter power consumption , 2013, SIGMETRICS '13.

[36]  Sriram Sankar,et al.  The need for speed and stability in data center power capping , 2012, 2012 International Green Computing Conference (IGCC).

[37]  Shaolei Ren,et al.  Colocation Demand Response: Why Do I Turn Off My Servers? , 2014, ICAC.