Advertisement

Double-Sided Auction Games for Efficient Resource Allocation

  • Zhongjing MaEmail author
  • Suli Zou
Chapter
  • 9 Downloads

Abstract

With an effort to allocate divisible resources among suppliers and consumers, a double-sided auction model is designed to decide strategies for individual players in this chapter. Under the auction mechanism with the VCG-type payment, the incentive compatibility holds, and the efficient bid profile is a Nash equilibrium (NE). Different from the single-sided auction in the previous chapter, there exists an infinite number of NEs in the underlying double-sided auction game, which brings difficulties for players to implement the efficient solution. To overcome this challenge, we formulate the double-sided auction game as a pair of single-sided auction games which are coupled via a joint potential quantity of the resource. A decentralized iteration procedure is then designed to achieve efficient solution, where a single player, a buyer or a seller, implements his best strategy with respect to a given potential quantity and a constraint on his bid strategy. Accordingly, the potential quantity is updated with respect to iteration steps as well. It is verified that the system converges to the efficient NE within finite iteration steps in the order of \(\mathscr {O}(\ln (1/\varepsilon ))\) with \(\varepsilon \) representing the termination criterion of the algorithm.

References

  1. 1.
    R. Jain, J. Walrand, An efficient Nash-implementation mechanism for network resource allocation. Automatica 46, 1276–1283 (2010)MathSciNetCrossRefGoogle Scholar
  2. 2.
    G. Iosifidis, I. Koutsopoulos, Double auction mechanisms for resource allocation in autonomous networks. IEEE J. Sel. Areas Commun. 28(1), 95–102 (2010)CrossRefGoogle Scholar
  3. 3.
    S.K. Garg, S. Venugopal, J. Broberg, R. Buyya, Double auction-inspired meta-scheduling of parallel applications on global grids. J. Parallel Distrib. Comput. 73(4), 450–464 (2013)Google Scholar
  4. 4.
    A.R. Kian, J.B. Cruz, R.J. Thomas, Bidding strategies in oligopolistic dynamic electricity double-sided auctions. IEEE Trans. Power Syst. 20(1), 50–58 (2005)CrossRefGoogle Scholar
  5. 5.
    P. Samimi, Y. Teimouri, M. Mukhtar, A combinatorial double auction resource allocation model in cloud computing. Inf. Sci. 357, 201–216 (2016)CrossRefGoogle Scholar
  6. 6.
    A. Mohsenian-Rad, V.W.S. Wong, J. Jatskevich, R. Schober, A. Leon-Garcia, Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans. Smart Grid 1(3), 320–331 (2010)CrossRefGoogle Scholar
  7. 7.
    R. Johari, J.N. Tsitsiklis, Communication requirements of VCG-like mechanisms in convex environments, in Proceedings of the Allerton Conference on Control, Communications and Computing, Princeton, pp. 1391–1396Google Scholar
  8. 8.
    S. Yang, B. Hajek, VCG-Kelly mechanisms for allocation of divisible goods: adapting VCG mechanisms to one-dimensional signals. IEEE J. Sel. Areas Commun. 25(6), 1237–1243 (2007)Google Scholar
  9. 9.
    P. Samadi, H. Mohsenian-Rad, R. Schober, V.W.S. Wong, Advanced demand side management for the future smart grid using mechanism design. IEEE Trans. Smart Grid 3(3), 1170–1180 (2012)CrossRefGoogle Scholar
  10. 10.
    D. Fang, W. Jingfang, D. Tang, A double auction model for competitive generators and large consumers considering power transmission cost. Int. J. Electr. Power Energy Syst. 43(1), 880–888 (2012)CrossRefGoogle Scholar
  11. 11.
    P.K. Tiwari, Y.R. Sood, An efficient approach for optimal allocation and parameters determination of TCSC with investment cost recovery under competitive power market. IEEE Trans. Power Syst. 28(3), 2475–2484 (2013)CrossRefGoogle Scholar
  12. 12.
    X. Zou, Double-sided auction mechanism design in electricity based on maximizing social welfare. Energy Policy 37, 4231–4239 (2009)CrossRefGoogle Scholar
  13. 13.
    R.T. Maheswaran, T. Basar, Social welfare of selfish agents: motivating efficiency for divisible resources, in IEEE 43rd Annual Conference on Decision and Control, vol. 2 (2004), pp. 1550–1555Google Scholar
  14. 14.
    A. Lazar, N. Semret, Design and analysis of the progressive second price auction for network bandwidth sharing. Telecommun. Syst. 13 (2001)Google Scholar
  15. 15.
    N. Semret, Market Mechanisms for network resource sharing. Ph.D. thesis, Columbia University (1999)Google Scholar
  16. 16.
    B. Tuffin, Revisited progressive second price auction for charging telecommunication networks. Telecommun. Syst. 20(3–4), 255–263 (2002)CrossRefGoogle Scholar
  17. 17.
    P. Maillé, B. Tuffin, The progressive second price mechanism in a stochastic environment. Netnomics 5(2), 119–147 (2003)CrossRefGoogle Scholar
  18. 18.
    P. Maillé, Market clearing price and equilibria of the progressive second price mechanism. RAIRO-Oper. Res. 41(4), 465–478 (2007)MathSciNetCrossRefGoogle Scholar
  19. 19.
    S. Zou, Z. Ma, X. Liu, Auction-based distributed efficient economic operations of microgrid systems. Int. J. Control 87(12), 2446–2462 (2014)MathSciNetCrossRefGoogle Scholar
  20. 20.
    X. Shi, Z. Ma, An efficient game for vehicle-to-grid coordination problems in smart grid. Int. J. Syst. Sci. 46(15), 2686–2701 (2015)MathSciNetCrossRefGoogle Scholar
  21. 21.
    J. Zou, X. Hongwan, Auction-based power allocation for multiuser two-way relaying networks. IEEE Trans. Wirel. Commun. 12(1), 31–39 (2013)CrossRefGoogle Scholar
  22. 22.
    L. Cao, W. Xu, J. Lin, K. Niu, Z. He, An auction approach to resource allocation in OFDM-based cognitive radio networks, in 75th IEEE Vehicular Technology Conference (VTC Spring), Yokohama (2012), pp. 1–5Google Scholar
  23. 23.
    D. Wu, Y. Cai, M. Guizani, Auction-based relay power allocation: Pareto optimality, fairness, and convergence. IEEE Trans. Commun. 62(7), 2249–2259 (2014)Google Scholar
  24. 24.
    D.C. Parkes, L.H. Ungar, Iterative combinatorial auctions: theory and practice, in 17th National Conference on Artificial Intelligence (AAAI-00) (2000), pp. 74–81Google Scholar
  25. 25.
    L.M. Ausubel, P. Milgrom, Ascending auctions with package bidding. Front. Theor. Econ. 1, 1–42 (2002)MathSciNetCrossRefGoogle Scholar
  26. 26.
    P. Maillé, B. Tuffin, Multibid auctions for bandwidth allocation in communication networks, in 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 1 (2004), pp. 54–65Google Scholar
  27. 27.
    P. Maillé, B. Tuffin, Pricing the internet with multibid auctions. IEEE/ACM Trans. Netw. 14(5), 992–1004 (2006)CrossRefGoogle Scholar
  28. 28.
    P. Jia, C.W. Qu, P.E. Caines, On the rapid convergence of a class of decentralized decision processes: quantized progressive second-price auctions. IMA J. Math. Control. Inf. 26(3), 325–355 (2009)MathSciNetCrossRefGoogle Scholar
  29. 29.
    P. Jia, P. Caines, Analysis of quantized double auctions with application to competitive electricity markets. INFOR: Inf. Syst. Oper. Res. 48(4), 239–250 (2010)Google Scholar
  30. 30.
    P. Jia, P.E. Caines, Analysis of decentralized quantized auctions on cooperative networks. IEEE Trans. Autom. Control 58(2), 529–534 (2013)MathSciNetCrossRefGoogle Scholar
  31. 31.
    S. Boyd, L. Vandenberghe, Convex Optimization (Cambridge University Press, Cambridge, 2004)Google Scholar
  32. 32.
    D.S. Damianov, J.G. Becker, Auctions with variable supply: Uniform price versus discriminatory. Eur. Econ. Rev. 54(4), 571–593 (2010)Google Scholar
  33. 33.
    H. Haghighat, H. Seifi, A.R. Kian, Pay-as-bid versus marginal pricing: the role of suppliers strategic behavior. Electr. Power Energy Syst. 42(1), 350–358 (2012)Google Scholar
  34. 34.
    D.E. Aliabadi, M. Kaya, G. Sahin, An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms. Energy Policy 100, 191–205 (2017)CrossRefGoogle Scholar
  35. 35.
    S. Zhou, Z. Shu, K. Tan, H.B. Gooi, S. Chen, Y. Gao, Study of market clearing model for Singapore’s wholesale real-time electricity market, in IEEE International Conference on Power System Technology (2016), pp. 1–7Google Scholar
  36. 36.
    M. Nazif Faqiry and Sanjoy Das, Double-sided energy auction in microgrid: equilibrium under price anticipation. IEEE J. Mag. 4, 3794–3805 (2016)Google Scholar
  37. 37.
    Y. Wang, W. Saad, Z. Han, H. Vincent Poor, T. Basar, A game-theoretic approach to energy trading in the smart grid. IEEE Trans. Smart Grid 5(3), 1439–1450 (2014)Google Scholar
  38. 38.
    A. Jin, W. Song, W. Zhuang, Auction-based resource allocation for sharing cloudlets in mobile cloud computing. IEEE Trans. Emerg. Top. Comput. PP(99), 1 (2017)Google Scholar
  39. 39.
    H. Zhou, J. Jiang, W. Zeng, An agent-based finance market model with the continuous double auction mechanism. Second WRI Glob. Congr. Intell. Syst. 2, 316–319 (2010)Google Scholar
  40. 40.
    H. Kebriaei, B. Maham, D. Niyato, Double-sided bandwidth-auction game for cognitive device-to-device communication in cellular networks. IEEE Trans. Veh. Technol. 65(9), 7476–7487 (2016)CrossRefGoogle Scholar
  41. 41.
    P. Li, S. Guo, I. Stojmenovic, A truthful double auction for device-to-device communications in cellular networks. IEEE J. Sel. Areas Commun. 34(1), 71–81 (2016)CrossRefGoogle Scholar
  42. 42.
    W. Dong, S. Rallapalli, L. Qiu, K.K. Ramakrishnan, Y. Zhang, Double auctions for dynamic spectrum allocation. IEEE/ACM Trans. Netw. 24(4), 2485–2497 (2016)CrossRefGoogle Scholar
  43. 43.
    E. Bompard, Y. Ma, R. Napoli, G. Abrate, The demand elasticity impacts on the strategic bidding behavior of the electricity producers. IEEE Trans. Power Syst. 22(1), 188–197 (2007)CrossRefGoogle Scholar
  44. 44.
    F.S. Wen, A.K. David, Strategic bidding for electricity supply in a day-ahead energy market. Electr. Power Syst. Res. 59, 197–206 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of AutomationBeijing Institute of TechnologyBeijingChina

Personalised recommendations