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48
Competitive Auctions
, 2002
"... We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of ..."
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Cited by 83 (10 self)
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We study a class of singleround, sealedbid auctions for items in unlimited supply, such as digital goods. We introduce the notion of competitive auctions. A competitive auction is truthful (i.e., encourages buyers to bid their utility) and yields profit that is roughly within a constant factor of the profit of optimal fixed pricing for all inputs. We justify the use of optimal fixed pricing as a benchmark for evaluating competitive auction profit. We show that several randomized auctions are truthful and competitive and that no truthful deterministic auction is competitive. Our results extend to bounded supply markets, for which we also get truthful and competitive auctions.
How Much Can Taxes Help Selfish Routing?
 EC'03
, 2003
"... ... in networks. We consider a model of selfish routing in which the latency experienced by network tra#c on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route tra#c on minimumlatency paths. The quality of a routing of tra#c is historically ..."
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Cited by 68 (5 self)
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... in networks. We consider a model of selfish routing in which the latency experienced by network tra#c on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route tra#c on minimumlatency paths. The quality of a routing of tra#c is historically measured by the sum of all travel times, also called the total latency. It is well known
Simple versus Optimal Mechanisms
"... The monopolist’s theory of optimal singleitem auctions for agents with independent private values can be summarized by two statements. The first is from Myerson [8]: the optimal auction is Vickrey with a reserve price. The second is from Bulow and Klemperer [1]: it is better to recruit one more bid ..."
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Cited by 47 (16 self)
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The monopolist’s theory of optimal singleitem auctions for agents with independent private values can be summarized by two statements. The first is from Myerson [8]: the optimal auction is Vickrey with a reserve price. The second is from Bulow and Klemperer [1]: it is better to recruit one more bidder and run the Vickrey auction than to run the optimal auction. These results hold for singleitem auctions under the assumption that the agents ’ valuations are independently and identically drawn from a distribution that satisfies a natural (and prevalent) regularity condition. These fundamental guarantees for the Vickrey auction fail to hold in general singleparameter agent mechanism design problems. We give precise (and weak) conditions under which approximate analogs of these two results hold, thereby demonstrating that simple mechanisms remain almost optimal in quite general singleparameter agent settings.
Optimal mechanism design and money burning
 STOC ’08
, 2008
"... Mechanism design is now a standard tool in computer science for aligning the incentives of selfinterested agents with the objectives of a system designer. There is, however, a fundamental disconnect between the traditional application domains of mechanism design (such as auctions) and those arising ..."
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Cited by 42 (12 self)
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Mechanism design is now a standard tool in computer science for aligning the incentives of selfinterested agents with the objectives of a system designer. There is, however, a fundamental disconnect between the traditional application domains of mechanism design (such as auctions) and those arising in computer science (such as networks): while monetary transfers (i.e., payments) are essential for most of the known positive results in mechanism design, they are undesirable or even technologically infeasible in many computer systems. Classical impossibility results imply that the reach of mechanisms without transfers is severely limited. Computer systems typically do have the ability to reduce service quality—routing systems can drop or delay traffic, scheduling protocols can delay the release of jobs, and computational payment schemes can require computational payments from users (e.g., in spamfighting systems). Service degradation is tantamount to requiring that users burn money, and such “payments ” can be used to influence the preferences of the agents at a cost of degrading the social surplus. We develop a framework for the design and analysis of moneyburning mechanisms to maximize the residual surplus— the total value of the chosen outcome minus the payments required. Our primary contributions are the following. • We define a general template for priorfree optimal mechanism design that explicitly connects Bayesian optimal mechanism design, the dominant paradigm in economics, with worstcase analysis. In particular, we establish a general and principled way to identify appropriate performance benchmarks in priorfree mechanism design. • For general singleparameter agent settings, we char
Setting lower bounds on truthfulness
 In Proceedings of the Eighteenth Annual ACMSIAM Symposium on Discrete Algorithms (SODA
, 2007
"... We present and discuss general techniques for proving inapproximability results for truthful mechanisms. We make use of these techniques to prove lower bounds on the approximability of several nonutilitarian multiparameter problems. In particular, we demonstrate the strength of our techniques by e ..."
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Cited by 30 (4 self)
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We present and discuss general techniques for proving inapproximability results for truthful mechanisms. We make use of these techniques to prove lower bounds on the approximability of several nonutilitarian multiparameter problems. In particular, we demonstrate the strength of our techniques by exhibiting a lower bound of 2 − 1 m for the scheduling problem with unrelated machines (formulated as a mechanism design problem in the seminal paper of Nisan and Ronen on Algorithmic Mechanism Design). Our lower bound applies to truthful randomized mechanisms (disregarding any computational assumptions on the running time of these mechanisms). Moreover, it holds even for the weaker notion of truthfulness for randomized mechanisms – i.e., truthfulness in expectation. This lower bound nearly matches the known 7 4 (randomized) truthful upper bound for the case of two machines (a nontruthful FPTAS exists). No lower bound for truthful randomized mechanisms in multiparameter settings was previously known. We show an application of our techniques to the workloadminimization problem in networks. We prove our lower bounds for this problem in the interdomain routing setting presented by Feigenbaum, Papadimitriou, Sami, and Shenker. Finally, we discuss several notions of nonutilitarian “fairness ” (MaxMin fairness, MinMax fairness, and envy minimization). We show how our techniques can be used to prove lower bounds for these notions.
Budget Feasible Mechanisms
"... Abstract—We study a novel class of mechanism design problems in which the outcomes are constrained by the payments. This basic class of mechanism design problems captures many common economic situations, and yet it has not been studied, to our knowledge, in the past. We focus on the case of procurem ..."
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Cited by 15 (4 self)
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Abstract—We study a novel class of mechanism design problems in which the outcomes are constrained by the payments. This basic class of mechanism design problems captures many common economic situations, and yet it has not been studied, to our knowledge, in the past. We focus on the case of procurement auctions in which sellers have private costs, and the auctioneer aims to maximize a utility function on subsets of items, under the constraint that the sum of the payments provided by the mechanism does not exceed a given budget. Standard mechanism design ideas such as the VCG mechanism and its variants are not applicable here. We show that, for general functions, the budget constraint can render mechanisms arbitrarily bad in terms of the utility of the buyer. However, our main result shows that for the important class of submodular functions, a bounded approximation ratio is achievable. Better approximation results are obtained for subclasses of the submodular functions. We explore the space of budget feasible mechanisms in other domains and give a characterization under more restricted conditions. I.
Revenue Submodularity
 EC'09
, 2009
"... We introduce revenue submodularity, the property that market expansion has diminishing returns on an auction’s expected revenue. We prove that revenue submodularity is generally possible only in matroid markets, that Bayesianoptimal auctions are always revenuesubmodular in such markets, and that t ..."
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Cited by 12 (6 self)
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We introduce revenue submodularity, the property that market expansion has diminishing returns on an auction’s expected revenue. We prove that revenue submodularity is generally possible only in matroid markets, that Bayesianoptimal auctions are always revenuesubmodular in such markets, and that the VCG mechanism is revenuesubmodular in matroid markets with i.i.d. bidders and “sufficient competition”. We also give two applications of revenue submodularity: good approximation algorithms for novel market expansion problems, and approximate revenue guarantees for the VCG mechanism with i.i.d. bidders.
MobiCent: a CreditBased Incentive System for Disruption Tolerant Network
"... When Disruption Tolerant Network (DTN) is used in commercial environments, incentive mechanism should be employed to encourage cooperation among selfish mobile users. Key challenges in the design of an incentive scheme for DTN are that disconnections among nodes are the norm rather than exception an ..."
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Cited by 11 (0 self)
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When Disruption Tolerant Network (DTN) is used in commercial environments, incentive mechanism should be employed to encourage cooperation among selfish mobile users. Key challenges in the design of an incentive scheme for DTN are that disconnections among nodes are the norm rather than exception and network topology is time varying. Thus, it is difficult to detect selfish actions that can be launched by mobile users or to predetermine the routing path to be used. In this paper, we propose MobiCent, a creditbased incentive system for DTN. While MobiCent allows the underlying routing protocol to discover the most efficient paths, it is also incentive compatible. Therefore, using MobiCent, rational nodes will not purposely waste transfer opportunity or cheat by creating nonexisting contacts to increase their rewards. MobiCent also provides different payment mechanisms to cater to client that wants to minimize either payment or data delivery delay.
OURS: Optimal Unicast Routing Systems in NonCooperative Wireless Networks
 MOBICOM'06
, 2006
"... We propose novel solutions for unicast routing in wireless networks consisted of selfish terminals: in order to alleviate the inevitable overpayment problem (and thus economic inefficiency) of the VCG (VickreyClarkGroves) mechanism, we design a mechanism that results in Nash equilibria rather tha ..."
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Cited by 11 (0 self)
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We propose novel solutions for unicast routing in wireless networks consisted of selfish terminals: in order to alleviate the inevitable overpayment problem (and thus economic inefficiency) of the VCG (VickreyClarkGroves) mechanism, we design a mechanism that results in Nash equilibria rather than the traditional strategyproofness (using weakly dominant strategy). In addition, we systematically study the unicast routing system in which both the relay terminals and the service requestor (either the source or the destination nodes or both) could be selfish. To the best of our knowledge, this is the first paper that presents social efficient unicast routing systems with proved performance guarantee. Thus, we call the proposed systems: Optimal Unicast Routing Systems (OURS). Our main contributions of OURS are as follows. (1) For the principal model where the service requestor is not selfish, we propose a
The Stackelberg Minimum Spanning Tree Game
 In Proc. of 10th WADS
, 2007
"... Abstract. We consider a oneround twoplayer network pricing game, the Stackelberg Minimum Spanning Tree game or StackMST. The game is played on a graph (representing a network), whose edges are colored either red or blue, and where the red edges have a given fixed cost (representing the competitor’ ..."
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Cited by 10 (1 self)
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Abstract. We consider a oneround twoplayer network pricing game, the Stackelberg Minimum Spanning Tree game or StackMST. The game is played on a graph (representing a network), whose edges are colored either red or blue, and where the red edges have a given fixed cost (representing the competitor’s prices). The first player chooses an assignment of prices to the blue edges, and the second player then buys the cheapest possible minimum spanning tree, using any combination of red and blue edges. The goal of the first player is to maximize the total price of purchased blue edges. This game is the minimum spanning tree analog of the wellstudied Stackelberg shortestpath game. We analyze the complexity and approximability of the first player’s best strategy in StackMST. In particular, we prove that the problem is APXhard even if there are only two different red costs, and give an approximation algorithm whose approximation ratio is at most min{k, 3 + 2 ln b, 1 + ln W}, where k is the number of distinct red costs, b is the number of blue edges, and W is the maximum ratio between red costs. We also give a natural integer linear programming formulation of the problem, and show that the integrality gap of the fractional relaxation asymptotically matches the approximation guarantee of our algorithm. 1