TY - GEN
T1 - On Fair Attribution of Costs under Peak-Based Pricing to Cloud Tenants
AU - Nasiriani, Neda
AU - Wang, Cheng
AU - Kesidis, George
AU - Urgaonkar, Bhuvan
AU - Chen, Lydia Y.
AU - Birke, Robert
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/16
Y1 - 2015/11/16
N2 - The costs incurred by cloud providers towards operating their data centers are often determined in large part by their peak demands. The pricing schemes currently used by cloud providers to recoup these costs from their tenants, however, do not distinguish tenants based on their contributions to the cloud's overall peak demand. Using the concrete example of peak-based pricing as employed by many electric utility companies, we show that this 'gap' may lead to unfair attribution of costs to the tenants. Simple enhancements of existing cloud pricing (e.g., analogous to the coincident peak pricing (CPP) used by some electric utilities) do not adequately address these shortcomings and suffer from short-term unfairness and undesirable oscillatory price vs. demand relationship offered to tenants. To overcome these shortcomings, we define an alternative pricing scheme to more fairly distribute a cloud's costs among its tenants. Our approach to fair attribution of cloud's costs is inspired by the concept of Shapley values used to fairly divide revenue among participants of a financial coalition. We demonstrate the efficacy of our scheme under price-sensitive tenant demand response using a combination of (i) extensive empirical evaluation with recent workloads from commercial data centers operated by IBM, and (ii) analytical modeling through non-cooperative game theory for a special case of tenant demand model.
AB - The costs incurred by cloud providers towards operating their data centers are often determined in large part by their peak demands. The pricing schemes currently used by cloud providers to recoup these costs from their tenants, however, do not distinguish tenants based on their contributions to the cloud's overall peak demand. Using the concrete example of peak-based pricing as employed by many electric utility companies, we show that this 'gap' may lead to unfair attribution of costs to the tenants. Simple enhancements of existing cloud pricing (e.g., analogous to the coincident peak pricing (CPP) used by some electric utilities) do not adequately address these shortcomings and suffer from short-term unfairness and undesirable oscillatory price vs. demand relationship offered to tenants. To overcome these shortcomings, we define an alternative pricing scheme to more fairly distribute a cloud's costs among its tenants. Our approach to fair attribution of cloud's costs is inspired by the concept of Shapley values used to fairly divide revenue among participants of a financial coalition. We demonstrate the efficacy of our scheme under price-sensitive tenant demand response using a combination of (i) extensive empirical evaluation with recent workloads from commercial data centers operated by IBM, and (ii) analytical modeling through non-cooperative game theory for a special case of tenant demand model.
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U2 - 10.1109/MASCOTS.2015.23
DO - 10.1109/MASCOTS.2015.23
M3 - Conference contribution
AN - SCOPUS:84962248855
T3 - Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
SP - 51
EP - 60
BT - Proceedings - IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2015
PB - IEEE Computer Society
T2 - IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2015
Y2 - 5 October 2015 through 7 October 2015
ER -