A Framework for Expansion Planning of Data Centers in Electricity and Data Networks Under Uncertainty

This paper presents the expansion planning for data centers and data routes in the data and electricity networks considering the uncertainties in the planning horizon to ensure an acceptable rate of service to the requests received from the end-users in the data network. The objective is to determine the location and capacity of the data centers as well as the required data routes while considering the imposed constraints in the electricity and data networks. The installation cost of data centers and data routes, as well as the expected operation cost of the data centers, are minimized. The proposed problem addressed the uncertainties in the expansion planning of the electricity networks including the availability of renewable generation resources, the variations in electricity demand, the availability of generation and transmission components in the electricity network, and the uncertainties in the number of requests received by the user groups in the data network. The problem is formulated as a mixed integer linear programming problem and Bender decomposition and electricity price signals are used to capture the interaction among the data and electricity networks. The presented case study shows the effectiveness of the proposed approach.

[1]  Nikos D. Hatziargyriou,et al.  Transmission Expansion Planning of Systems With Increasing Wind Power Integration , 2013, IEEE Transactions on Power Systems.

[2]  Sergiu Nedevschi,et al.  Reducing Network Energy Consumption via Sleeping and Rate-Adaptation , 2008, NSDI.

[3]  J. Dupacová,et al.  Scenario reduction in stochastic programming: An approach using probability metrics , 2000 .

[4]  Zhi Zhou,et al.  Pricing Bilateral Electricity Trade between Smart Grids and Hybrid Green Datacenters , 2015, SIGMETRICS.

[5]  Xue Liu,et al.  A Survey on Geographic Load Balancing Based Data Center Power Management in the Smart Grid Environment , 2014, IEEE Communications Surveys & Tutorials.

[6]  Longjun Liu,et al.  Enabling datacenter servers to scale out economically and sustainably , 2013, 2013 46th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[7]  Minghua Chen,et al.  Balance your bids before your bits: the economics of geographic load-balancing , 2014, e-Energy.

[8]  Hamed Mohsenian Rad,et al.  Profit maximization and power management of green data centers supporting multiple slas , 2013, 2013 International Conference on Computing, Networking and Communications (ICNC).

[9]  Lachlan L. H. Andrew,et al.  Geographical load balancing with renewables , 2011, PERV.

[10]  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).

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

[12]  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).

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

[14]  Hai Jin,et al.  MultiGreen: cost-minimizing multi-source datacenter power supply with online control , 2013, e-Energy '13.

[15]  Tamil Nadu,et al.  Estimation of Weibull Parameters for Wind speed calculation at Kanyakumari in India , 2014 .

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

[17]  A. Wierman,et al.  Characterizing the impact of the workload on the value of dynamic resizing in data centers , 2012, 2013 Proceedings IEEE INFOCOM.

[18]  B. Lankl,et al.  111-Gb/s POLMUX-RZ-DQPSK transmission over 1140 km of SSMF with 10.7-Gb/s NRZ-OOK neighbours , 2008, 2008 34th European Conference on Optical Communication.

[19]  Margaret Martonosi,et al.  Dynamic thermal management for high-performance microprocessors , 2001, Proceedings HPCA Seventh International Symposium on High-Performance Computer Architecture.

[20]  Yong Fu,et al.  Dynamic Energy Management for the Smart Grid With Distributed Energy Resources , 2013, IEEE Transactions on Smart Grid.

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

[22]  Bo Li,et al.  Fuel Cell Generation in Geo-Distributed Cloud Services: A Quantitative Study , 2014, 2014 IEEE 34th International Conference on Distributed Computing Systems.

[23]  Ricardo Bianchini,et al.  Conserving disk energy in network servers , 2003, ICS '03.

[24]  D.O. Koval,et al.  Assessment of Transmission-Line Common-Mode, Station-Originated, and Fault-Type Forced-Outage Rates , 2010, IEEE Transactions on Industry Applications.

[25]  A. Vafamehr,et al.  Expansion planning of data centers in energy and cyber networks , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

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

[27]  Yuan Yao,et al.  Data centers power reduction: A two time scale approach for delay tolerant workloads , 2012, 2012 Proceedings IEEE INFOCOM.

[28]  Yves Gagnon,et al.  An Analysis of Wind Speed Distribution at Thasala, Nakhon Si Thammarat, Thailand , 2011 .

[29]  Yong Fu,et al.  Benders decomposition: applying Benders decomposition to power systems , 2005 .

[30]  Hai Jin,et al.  Carbon-Aware Load Balancing for Geo-distributed Cloud Services , 2013, 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems.

[31]  Xue Liu,et al.  OptiTuner: On Performance Composition and Server Farm Energy Minimization Application , 2011, IEEE Transactions on Parallel and Distributed Systems.

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

[33]  Roger Smith,et al.  Computing in the Cloud , 2009 .

[34]  Andrew Warfield,et al.  Live migration of virtual machines , 2005, NSDI.