Abstract
Data centers are key participants in emergency demand response (EDR), where the grid coordinates large electricity consumers for reducing their consumption during emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers (e.g., Google), this work studies EDR in multi-tenant colocation data centers (e.g., Equinix) where servers are owned and managed by individual tenants and which are better targets of EDR. Existing EDR mechanisms incentivize tenants’ energy reduction. Such designs can either be gamed by strategic tenants or untrustworthy colocation operators for illegal gains. These serious privacy concerns stand as barrier preventing the tenants’ participation in EDR. This chapter addresses such concerns by proposing a privacy-preserving and strategy-proof mechanism using the descending clock auction. Privacy is protected by implementing homomorphic encryption for aggregation through the clock auction, where operator can only know the aggregate of the tenants’ values or bids but not their individual private values or confidential information submitted to meet the EDR. We evaluate the privacy and performance of this scheme by formulating descending clock auction, in which the amount of energy/price the tenants are willing to reduce for a given price/energy to meet EDR is protected.
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References
O. Baranov, C. Aperjis, L.M. Ausubel, T. Morrill, Efficient procurement auctions with increasing returns. Am. Econ. J. Macroecon. 9(3), 1–27 (2017)
D. Bergemann, B.A. Brooks, S. Morris, Optimal auction design in a common value model. Cowles foundation discussion paper no. 2064 (2016)
J. Levin, A. Skrzypacz, Are dynamic Vickrey auctions practical? Properties of the combinatorial clock auction. Technical report, National Bureau of Economic Research (2014)
D. Liu, A. Bagh, New privacy-preserving ascending auction for assignment problems (Novemeber 1, 2015). Available at SSRN: https://ssrn.com/abstract=2883867
T.-D. Nguyen, T. Sandholm, Optimizing prices in descending clock auctions, in Proceedings of the Fifteenth ACM Conference on Economics and Computation, Stanford, June 2014, pp. 93–110
P. Paillier, Public-key cryptosystems based on composite degree residuosity classes, in Eurocrypt (Eurocrypt’99), Prague, Czech Republic, May 1999
R. Poudineh, T. Jamasb, Distributed generation, storage, demand response and energy efficiency as alternatives to grid capacity enhancement. Energy Policy 67, 222–231 (2014)
E. Shi, H. Chan, E. Rieffel, R. Chow, D. Song, Privacy-preserving aggregation of time-series data, in Annual Network & Distributed System Security Symposium (NDSS), San Diego, February 2011
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Pan, M., Wang, J., Errapotu, S.M., Zhang, X., Ding, J., Han, Z. (2019). Clock Auction Inspired Privacy Preservation in Colocation Data Centers. In: Big Data Privacy Preservation for Cyber-Physical Systems. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-13370-2_6
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DOI: https://doi.org/10.1007/978-3-030-13370-2_6
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