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33
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 37 (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
Designing networks with good equilibria
 In SODA ’08
, 2007
"... In a network with selfish users, designing and deploying a protocol determines the rules of the game by which end users interact with each other and with the network. We study the problem of designing a protocol to optimize the equilibrium behavior of the induced network game. We consider network co ..."
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Cited by 32 (4 self)
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In a network with selfish users, designing and deploying a protocol determines the rules of the game by which end users interact with each other and with the network. We study the problem of designing a protocol to optimize the equilibrium behavior of the induced network game. We consider network costsharing games, where the set of Nash equilibria depends fundamentally on the choice of an edge costsharing protocol. Previous research focused on the Shapley protocol, in which the cost of each edge is shared equally among its users. We systematically study the design of optimal costsharing protocols for undirected and directed graphs, singlesink and multicommodity networks, different classes of costsharing methods, and different measures of the inefficiency of equilibria. One of our main technical tools is a complete characterization of the uniform costsharing protocols—protocols that are designed without foreknowledge of or assumptions on the network in which they will be deployed. We use this characterization result to identify the optimal uniform protocol in several scenarios: for example, the Shapley protocol is optimal in directed graphs, while the optimal protocol in undirected graphs, a simple priority scheme, has exponentially smaller worstcase price of anarchy than the Shapley protocol. We also provide several matching upper and lower bounds on the bestpossible performance of nonuniform costsharing protocols.
(Almost) optimal coordination mechanisms for unrelated maching scheduling
 IN 18TH ACMSIAM SYMP. ON DISCRETE ALGORITHMS (SODA
, 2008
"... We investigate the influence of different algorithmic choices on the approximation ratio in selfish scheduling. Our goal is to design local policies that minimize the inefficiency of resulting equilibria. In particular, we design optimal coordination mechanisms for unrelated machine scheduling, and ..."
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Cited by 21 (4 self)
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We investigate the influence of different algorithmic choices on the approximation ratio in selfish scheduling. Our goal is to design local policies that minimize the inefficiency of resulting equilibria. In particular, we design optimal coordination mechanisms for unrelated machine scheduling, and improve the known approximation ratio from Θ(m) to Θ(log m), where m is the number of machines. A local policy for each machine orders the set of jobs assigned to it only based on parameters of those jobs. A strongly local policy only uses the processing time of jobs on the the same machine. We prove that the approximation ratio of any set of strongly local ordering policies in equilibria is at least Ω(m). In particular, it implies that the approximation ratio of a greedy shortestfirst algorithm for machine scheduling is at least Ω(m). This closes the gap between the known lower and upper bounds for this problem, and answers an open question raised by Ibarra and Kim [16], and Davis and Jaffe [10]. We then design a local ordering policy with the approximation ratio of Θ(log m) in equilibria, and prove that this policy is optimal among all local ordering policies. This policy orders the jobs in the nondecreasing order of their inefficiency, i.e, the ratio between the processing time on that machine over the minimum processing time. Finally, we show that best responses of players for the inefficiencybased policy may not converge to a pure Nash equilibrium, and present a Θ(log² m) policy for which we can prove fast convergence of best responses to pure Nash equilibria.
Efficient coordination mechanisms for unrelated machine scheduling
 In: Proc. AMCSIAM SODA
, 2009
"... We present three new coordination mechanisms for scheduling n selfish jobs on m unrelated machines. A coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. The scheduling policies induce a game ..."
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Cited by 11 (0 self)
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We present three new coordination mechanisms for scheduling n selfish jobs on m unrelated machines. A coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. The scheduling policies induce a game among the jobs and each job prefers to be scheduled on a machine so that its completion time is minimum given the assignments of the other jobs. We consider the maximum completion time among all jobs as the measure of the efficiency of schedules. The approximation ratio of a coordination mechanism quantifies the efficiency of pure Nash equilibria (price of anarchy) of the induced game. Our mechanisms are deterministic, local, and preemptive in the sense that the scheduling policy does not necessarily process
Scheduling selfish tasks: about the performance of truthful algorithms
"... This paper deals with problems which fall into the domain of selfish scheduling: a protocol is in charge of building a schedule for a set of tasks without directly knowing their length. The protocol gets these informations from agents who control the tasks. The aim of each agent is to minimize the c ..."
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Cited by 8 (6 self)
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This paper deals with problems which fall into the domain of selfish scheduling: a protocol is in charge of building a schedule for a set of tasks without directly knowing their length. The protocol gets these informations from agents who control the tasks. The aim of each agent is to minimize the completion time of her task while the protocol tries to minimize the maximal completion time. When an agent reports the length of her task, she is aware of what the others bid and also of the protocol’s algorithm. Then, an agent can bid a false value in order to optimize her individual objective function. With erroneous information, even the most efficient algorithm may produce unreasonable solutions. An algorithm is truthful if it prevents the selfish agents from lying about the length of their task. The central question in this paper is: “How efficient a truthful algorithm can be? We study the problem of scheduling selfish tasks on parallel identical machines. This question has been raised by Christodoulou et al [8] in a distributed system, but it is also relevant in centrally controlled systems. Without considering side payments, our goal is to give a picture of the performance under the condition of truthfulness.
Selfish task allocation
, 2003
"... Recently there has been a lot of interest in problems at the intersection of Game Theory, Economics, and Computer Science. For example, there are interesting developments concerning algorithms for equilibria and cost sharing, algorithmic mechanism design, and the efficiency of systems with selfish ..."
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Cited by 7 (1 self)
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Recently there has been a lot of interest in problems at the intersection of Game Theory, Economics, and Computer Science. For example, there are interesting developments concerning algorithms for equilibria and cost sharing, algorithmic mechanism design, and the efficiency of systems with selfish users [17]. In this note, I will focus on the last area and in particular on the price of anarchy of scheduling or task allocation. I will discuss the issues of this area, mention the central results, and suggest some open problems. This is definitely not a review paper: My aim is to stimulate the reader, not to provide complete coverage of the area. The presentation favors simplicity to preciseness, examples to formal presentation, and intuition to rigor.
An algorithmic game theory primer
, 2008
"... We give a brief and biased survey of the past, present, and future of research on the interface of theoretical computer science and game theory. 1 ..."
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Cited by 5 (0 self)
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We give a brief and biased survey of the past, present, and future of research on the interface of theoretical computer science and game theory. 1
Designing Network Protocols for Good Equilibria
, 2009
"... Designing and deploying a network protocol determines the rules by which end users interact with each other and with the network. We consider the problem of designing a protocol to optimize the equilibrium behavior of a network with selfish users. We consider network costsharing games, where the set ..."
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Cited by 5 (1 self)
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Designing and deploying a network protocol determines the rules by which end users interact with each other and with the network. We consider the problem of designing a protocol to optimize the equilibrium behavior of a network with selfish users. We consider network costsharing games, where the set of Nash equilibria depends fundamentally on the choice of an edge costsharing protocol. Previous research focused on the Shapley protocol, in which the cost of each edge is shared equally among its users. We systematically study the design of optimal costsharing protocols for undirected and directed graphs, singlesink and multicommodity networks, and different measures of the inefficiency of equilibria. Our primary technical tool is a precise characterization of the costsharing protocols that only induce network games with purestrategy Nash equilibria. We use this characterization to prove, among other results, that the Shapley protocol is optimal in directed graphs, and that simple priority protocols are essentially optimal in undirected graphs.
The efficiency of optimal taxes
 In Combinatorial and Algorithmic Aspects of Networking, First Workshop on Combinatorial and Algorithmic Aspects of Networking (CAAN
, 2004
"... Abstract. It is well known that the selfish behavior of users in a network can be regulated through the imposition of the socalled optimal taxes on the network edges. Any traffic equilibrium reached by the selfish users who are conscious of both the travel latencies and the taxes will minimize the ..."
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Cited by 5 (2 self)
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Abstract. It is well known that the selfish behavior of users in a network can be regulated through the imposition of the socalled optimal taxes on the network edges. Any traffic equilibrium reached by the selfish users who are conscious of both the travel latencies and the taxes will minimize the social cost, i.e., will minimize the total latency. Optimal taxes incur desirable behavior from the society point of view but they cause disutility to the network users since the users ’ total cost is in general increased [4]. Excessive disutility due to taxation may be undesirable from the societal perspective as well. In this work we examine the efficiency of taxation as a mechanism for achieving the desired goal of minimizing the social cost. We show that for large classes of latency functions the total disutility due to taxation that is caused to the users and/or the system is bounded with respect to the social optimum. In addition, we show that if the social cost takes into account both the total latency and the total taxation in the network, the coordination ratio for certain latency functions is better than the coordination ratio when taxation is not used. 1