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Algorithmic mechanism design
 Games and Economic Behavior
, 1999
"... We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agen ..."
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Cited by 563 (17 self)
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We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own selfinterest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agents ’ interests are best served by behaving correctly. Following notions from the field of mechanism design, we suggest a framework for studying such algorithms. Our main technical contribution concerns the study of a representative task scheduling problem for which the standard mechanism design tools do not suffice. Journal of Economic Literature
Modular Competitiveness for Distributed Algorithms
 In Proc. 28th ACM Symp. on Theory of Computing (STOC
, 2000
"... We define a novel measure of competitive performance for distributed algorithms based on throughput, the number of tasks that an algorithm can carry out in a fixed amount of work. This new measure complements the latency measure of Ajtai et al. [3], which measures how quickly an algorithm can finish ..."
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Cited by 13 (2 self)
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We define a novel measure of competitive performance for distributed algorithms based on throughput, the number of tasks that an algorithm can carry out in a fixed amount of work. This new measure complements the latency measure of Ajtai et al. [3], which measures how quickly an algorithm can finish tasks that start at specified times. An important property of the throughput measure is that it is modular: we define a notion of relative competitiveness with the property that a krelatively competitive implementation of an object T using a subroutine U , combined with an lcompetitive implementation of U , gives a klcompetitive algorithm for ...
Analysing local algorithms in locationaware quasi unitdisk graphs
, 2011
"... Abstract. A local algorithm with local horizon r is a distributed algorithm that runs in r synchronous communication rounds; here r is a constant that does not depend on the size of the network. As a consequence, the output of a node in a local algorithm only depends on the input within r hops from ..."
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Cited by 1 (1 self)
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Abstract. A local algorithm with local horizon r is a distributed algorithm that runs in r synchronous communication rounds; here r is a constant that does not depend on the size of the network. As a consequence, the output of a node in a local algorithm only depends on the input within r hops from the node. We give tight bounds on the local horizon for a class of local algorithms for combinatorial problems on unitdisk graphs (UDGs). Most of our bounds are due to a refined analysis of existing approaches, while others are obtained by suggesting new algorithms. The algorithms we consider are based on network decompositions guided by a rectangular tiling of the plane. The algorithms are applied to matching, independent set, graph colouring, vertex cover, and dominating set. We also study local algorithms on quasiUDGs, which are a popular generalisation of UDGs, aimed at more realistic modelling of communication between the network nodes. Analysing the local algorithms on quasiUDGs