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Mechanism Design for Online Resource Allocation: A Unified Approach

Published: 12 June 2020 Publication History

Abstract

This paper concerns the mechanism design for online resource allocation in a strategic setting. In this setting, a single supplier allocates capacity-limited resources to requests that arrive in a sequential and arbitrary manner. Each request is associated with an agent who may act selfishly to misreport the requirement and valuation of her request. The supplier charges payment from agents whose requests are satisfied, but incurs a load-dependent supply cost. The goal is to design an incentive compatible online mechanism, which determines not only the resource allocation of each request, but also the payment of each agent, so as to (approximately) maximize the social welfare (i.e., aggregate valuations minus supply cost). We study this problem under the framework of competitive analysis. The major contribution of this paper is the development of a unified approach that achieves the best-possible competitive ratios for setups with different supply costs. Specifically, we show that when there is no supply cost or the supply cost function is linear, our model is essentially a standard 0-1 knapsack problem, for which our approach achieves logarithmic competitive ratios that match the state-of-the-art (which is optimal). For the more challenging setup when the supply cost is strictly-convex, we provide online mechanisms, for the first time, that lead to the optimal competitive ratios as well. To the best of our knowledge, this is the first approach that unifies the characterization of optimal competitive ratios in online resource allocation for different setups including zero, linear and strictly-convex supply costs.

References

[1]
Ravi P. Agarwal and V. Lakshmikantham. 1993. Uniqueness and Nonuniqueness Criteria for Ordinary Differential Equations .World Scientific.
[2]
Matthew. Andrews, Spyridon. Antonakopoulos, and Lisa. Zhang. 2016. Minimum-Cost Network Design with (Dis)economies of Scale. SIAM J. Comput., Vol. 45, 1 (2016), 49--66.
[3]
Vladimir Arnold. 1973. Ordinary differential equations. MIT Press.
[4]
Baruch Awerbuch, Yossi Azar, and Amir Epstein. 2005. The Price of Routing Unsplittable Flow. In Proceedings of the Thirty-seventh Annual ACM Symposium on Theory of Computing (STOC '05). ACM, New York, NY, USA, 57--66.
[5]
Y. Azar, N. Buchbinder, T. H. Chan, S. Chen, I. R. Cohen, A. Gupta, Z. Huang, N. Kang, V. Nagarajan, J. Naor, and D. Panigrahi. 2016. Online Algorithms for Covering and Packing Problems with Convex Objectives. In 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS), Vol. 00. 148--157.
[6]
Maria-Florina Balcan, Avrim Blum, and Yishay Mansour. 2008. Item Pricing for Revenue Maximization. In Proceedings of the 9th ACM Conference on Electronic Commerce (EC '08). ACM, New York, NY, USA, 50--59.
[7]
Yair Bartal, Rica Gonen, and Noam Nisan. 2003. Incentive Compatible Multi Unit Combinatorial Auctions. In Proceedings of the 9th Conference on Theoretical Aspects of Rationality and Knowledge (TARK '03). ACM, New York, NY, USA, 72--87.
[8]
Avrim Blum, Anupam Gupta, Yishay Mansour, and Ankit Sharma. 2011. Welfare and Profit Maximization with Production Costs. In Proceedings of the 2011 IEEE 52Nd Annual Symposium on Foundations of Computer Science (FOCS '11). Washington, DC, USA, 77--86.
[9]
Allan Borodin and Ran El-Yaniv. 1998. Online Computation and Competitive Analysis .Cambridge University Press, New York, NY, USA.
[10]
Jonathan M. Borwein and Adrian S. Lewis. 2006. Convex Analysis and and Nonlinear Optimization .Springer.
[11]
Niv Buchbinder and R. Gonen. 2015. Incentive Compatible Mulit-Unit Combinatorial Auctions: A Primal Dual Approach . Algorithmica, Vol. 72 (2015), 167--190.
[12]
Niv Buchbinder and Joseph Naor. 2006. Improved bounds for online routing and packing via a primal-dual approach. In 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06) . 293--304.
[13]
Niv Buchbinder and Joseph (Seffi) Naor. 2009. Online Primal-Dual Algorithms for Covering and Packing . Mathematics of Operations Research, Vol. 34, 2 (May 2009), 270--286.
[14]
Niv Buchbinder and Joseph (Seffi) Naor. 2009. The Design of Competitive Online Algorithms via a Primal-Dual Approach. Found. Trends Theor. Comput. Sci., Vol. 3, 2--3 (Feb. 2009), 93--263.
[15]
Ying-Ju Chen and Jiawei Zhang. 2012. Design of price mechanisms for network resource allocation via price of anarchy. Mathematical Programming, Vol. 131, 1 (01 Feb 2012), 333--364.
[16]
George Christodoulou and Elias Koutsoupias. 2005. The Price of Anarchy of Finite Congestion Games. In Proceedings of the Thirty-seventh Annual ACM Symposium on Theory of Computing (STOC '05). ACM, New York, NY, USA, 67--73.
[17]
José Correa, Patricio Foncea, Ruben Hoeksma, Tim Oosterwijk, and Tjark Vredeveld. 2017. Posted Price Mechanisms for a Random Stream of Customers. In Proc. of the ACM Conference on Economics and Computation .
[18]
Sven de Vries and Rakesh Vohra. 2003. Combinatorial Auctions: A Survey. INFORMS J. Comput., Vol. 15, 3 (2003), 284--309.
[19]
Nikhil R. Devanur and Thomas P. Hayes. 2009. The Adwords Problem: Online Keyword Matching with Budgeted Bidders Under Random Permutations. In Proceedings of the 10th ACM Conference on Electronic Commerce (EC '09). ACM, New York, NY, USA, 71--78.
[20]
Nikhil R. Devanur and Zhiyi Huang. 2017. Primal Dual Gives Almost Optimal Energy-Efficient Online Algorithms. ACM Trans. Algorithms, Vol. 14, 1, Article 5 (Dec. 2017).
[21]
Nikhil R. Devanur and Kamal Jain. 2012. Online Matching with Concave Returns. In Proceedings of the Forty-fourth Annual ACM Symposium on Theory of Computing (STOC '12). ACM, New York, NY, USA, 137--144.
[22]
Liran Einav, Chiara Farronato, Jonathan Levin, and Neel Sundaresan. 2018. Auctions versus Posted Prices in Online Markets. Journal of Political Economy, Vol. 126, 1 (2018), 18.
[23]
R. El-Yaniv, A. Fiat, R. M. Karp, and G. Turpin. 2001. Optimal search and one-way trading online algorithms . Algorithmica (New York), Vol. 30, 1 (2001), 101--139.
[24]
Anupam Gupta, Ravishankar Krishnaswamy, and Kirk Pruhs. 2013. Online Primal-Dual for Non-linear Optimization with Applications to Speed Scaling. In Approximation and Online Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg, 173--186.
[25]
Zhiyi Huang and Anthony Kim. 2015. Welfare Maximization with Production Costs: A Primal Dual Approach. In Proceedings of the Twenty-sixth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA '15). 59--72.
[26]
Navendu Jain, Ishai Menache, Joseph (Seffi) Naor, and Jonathan Yaniv. 2014. A Truthful Mechanism for Value-Based Scheduling in Cloud Computing. Theory of Computing Systems, Vol. 54, 3 (01 Apr 2014), 388--406.
[27]
Bala Kalyanasundaram and Kirk R. Pruhs. 2000. An Optimal Deterministic Algorithm for Online B-matching. Theor. Comput. Sci., Vol. 233, 1--2 (Feb. 2000), 319--325.
[28]
Qiulin Lin, Hanling Yi, John Pang, Minghua Chen, Adam Wierman, Michael Honig, and Yuanzhang Xiao. 2019. Competitive Online Optimization under Inventory Constraints. Proc. ACM Meas. Anal. Comput. Syst., Vol. 3, 1 (March 2019).
[29]
Will Ma and David Simchi-Levi. 2019. Tight Weight-dependent Competitive Ratios for Online Edge-weighted Bipartite Matching and Beyond. In Proceedings of the 2019 ACM Conference on Economics and Computation (EC '19). ACM, New York, NY, USA, 727--728.
[30]
Andreu Mas-Colell, Michael D. Whinston, and Jerry R. Green. 1995. Microeconomic Theory .Oxford University Press.
[31]
Aranyak Mehta. 2013. Online Matching and Ad Allocation. Found. Trends Theor. Comput. Sci., Vol. 8, 4 (Oct. 2013), 265--368.
[32]
Aranyak Mehta, Amin Saberi, Umesh Vazirani, and Vijay Vazirani. 2007. AdWords and Generalized Online Matching. J. ACM, Vol. 54, 5, Article 22 (Oct. 2007).
[33]
D. S. Mitrinović, J. E. Pevc arić, and A. M. Fink. 1991. Inequalities Involving Functions and Their Integrals and Derivatives. Springer Netherlands.
[34]
Noam Nisan, Tim Roughgarden, Éva Tardos, and Vijay V. Vazirani. 2007. Algorithmic Game Theory .Cambridge University Press, Cambridge, UK.
[35]
Lawrence Perko. 2001. Differential Equations and Dynamical Systems. Springer New York, New York, NY.
[36]
Andrei D. Polyanin and Valentin F. Zaitsev. 2003. Handbook of Exact Solutions for Ordinary Differential Equations. Chapman & Hall/CRC.
[37]
David Porter, Stephen Rassenti, Anil Roopnarine, and Vernon Smith. 2003. Combinatorial auction design. Proceedings of the National Academy of Sciences, Vol. 100, 19 (2003), 11153--11157. https://doi.org/10.1073/pnas.1633736100
[38]
Ryan Porter. 2004. Mechanism Design for Online Real-time Scheduling. In Proceedings of the 5th ACM Conference on Electronic Commerce (EC '04). ACM, New York, NY, USA, 61--70.
[39]
Xiaoqi Tan, Ablerto Leon-Garcia, and Danny .H.K. Tsang. 2019. Optimal Posted Prices for Online Resource Allocation with Supply Costs. In Proceedings of ACM Workshop on Mathematical Performance Modeling and Analysis . Phoenix, AZ, USA.
[40]
Ruqu Wang. 1993. Auctions versus Posted-Price Selling . The American Economic Review, Vol. 83, 4 (1993), 838--851.
[41]
Z. Zhang, Z. Li, and C. Wu. 2017. Optimal Posted Prices for Online Cloud Resource Allocation. Proc. ACM Meas. Anal. Comput. Syst., Vol. 1, 1 (June 2017).
[42]
Yunhong Zhou, Deeparnab Chakrabarty, and Rajan Lukose. 2008. Budget Constrained Bidding in Keyword Auctions and Online Knapsack Problems. In Proceedings of the 17th International Conference on World Wide Web (WWW '08). ACM, New York, NY, USA, 1243--1244.

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cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems
Proceedings of the ACM on Measurement and Analysis of Computing Systems  Volume 4, Issue 2
SIGMETRICS
June 2020
623 pages
EISSN:2476-1249
DOI:10.1145/3405833
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 12 June 2020
Online AM: 07 May 2020
Published in POMACS Volume 4, Issue 2

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Author Tags

  1. mechanism design
  2. online algorithms
  3. pricing
  4. resource allocation

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Cited By

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  • (2023)Near-optimal Online Algorithms for Joint Pricing and Scheduling in EV Charging NetworksProceedings of the 14th ACM International Conference on Future Energy Systems10.1145/3575813.3576878(72-83)Online publication date: 20-Jun-2023
  • (2023)Reinforcement learning based monotonic policy for online resource allocationFuture Generation Computer Systems10.1016/j.future.2021.09.023138:C(313-327)Online publication date: 1-Jan-2023
  • (2022)The Online Knapsack Problem with DeparturesProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/35706186:3(1-32)Online publication date: 8-Dec-2022
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