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Worstcase equilibria
 IN PROCEEDINGS OF THE 16TH ANNUAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE
, 1999
"... In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a ver ..."
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Cited by 847 (17 self)
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In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a
Q : Worstcase Fair Weighted Fair Queueing
"... The Generalized Processor Sharing (GPS) discipline is proven to have two desirable properties: (a) it can provide an endtoend boundeddelay service to a session whose traffic is constrained by a leaky bucket; (b) it can ensure fair allocation of bandwidth among all backlogged sessions regardless o ..."
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Cited by 365 (11 self)
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The Generalized Processor Sharing (GPS) discipline is proven to have two desirable properties: (a) it can provide an endtoend boundeddelay service to a session whose traffic is constrained by a leaky bucket; (b) it can ensure fair allocation of bandwidth among all backlogged sessions regardless of whether or not their traffic is constrained. The former property is the basis for supporting guaranteed service traffic while the later property is important for supporting besteffort service traffic. Since GPS uses an idealized fluid model which cannot be realized in the real world, various packet approximation algorithms of GPS have been proposed. Among these, Weighted Fair Queueing (WFQ) also known as Packet Generalized Processor Sharing (PGPS) has been considered to be the best one in terms of accuracy. In particular, it has been proven that the delay bound provided by WFQ is within one packet transmission time of that provided by GPS. In this paper, we will show that, contrary to pop...
Tight bounds for worstcase equilibria
 Proc. 13th SODA
, 2002
"... We study the problem of traffic routing in noncooperative networks. In such networks, users may follow selfish strategies to optimize their own performance measure and therefore their behavior does not have to lead to optimal performance of the entire network. In this paper we investigate the worst ..."
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Cited by 172 (5 self)
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the worstcase coordination ratio, which is a game theoretic measure aiming to reflect the price of selfish routing. Following a line of previous work, we focus on the most basic networks consisting of parallel links with linear latency functions. Our main result is that the worstcase coordination ratio
A WorstCase Worm
, 2004
"... Worms represent a substantial economic threat to the U.S. computing infrastructure. An important question is how much damage might be caused, as this figure can serve as a guide to evaluating how much to spend on defenses. We construct a parameterized worstcase analysis based on a simple damage mod ..."
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Cited by 32 (1 self)
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Worms represent a substantial economic threat to the U.S. computing infrastructure. An important question is how much damage might be caused, as this figure can serve as a guide to evaluating how much to spend on defenses. We construct a parameterized worstcase analysis based on a simple damage
Tradeoffs in worstcase equilibria
"... We investigate the problem of routing traffic through a congested network in an environment of noncooperative users. We use the worstcase coordination ratio suggested by Koutsoupias and Papadimitriou to measure the performance degradation due to the lack of a centralized traffic regulating authori ..."
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We investigate the problem of routing traffic through a congested network in an environment of noncooperative users. We use the worstcase coordination ratio suggested by Koutsoupias and Papadimitriou to measure the performance degradation due to the lack of a centralized traffic regulating
Typical versus Worst Case
, 1999
"... System design must address the typical needs and expectations of the user as well as the worst case use conditions. An approach is given and illustrated. Note this paper is still very incomplete. ..."
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System design must address the typical needs and expectations of the user as well as the worst case use conditions. An approach is given and illustrated. Note this paper is still very incomplete.
Worst Cases and Lattice Reduction
"... We propose a new algorithm to find worst cases for correct rounding of an analytic function. We first reduce this problem to the real small value problem — i.e. for polynomials with real coefficients. Then we show that this second problem can be solved efficiently, by extending Coppersmith’s work on ..."
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Cited by 12 (4 self)
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We propose a new algorithm to find worst cases for correct rounding of an analytic function. We first reduce this problem to the real small value problem — i.e. for polynomials with real coefficients. Then we show that this second problem can be solved efficiently, by extending Coppersmith’s work
Coalition Structure Generation with Worst Case Guarantees
, 1999
"... Coalition formation is a key topic in multiagent systems. One may prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. Furthermore, finding the optimal coalition ..."
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Cited by 270 (9 self)
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Coalition formation is a key topic in multiagent systems. One may prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. Furthermore, finding the optimal coalition structure is NPcomplete. But then, can the coalition structure found via a partial search be guaranteed to be within a bound from optimum? We show that none of the previous coalition structure generation algorithms can establish any bound because they search fewer nodes than a threshold that we show necessary for establishing a bound. We present an algorithm that establishes a tight bound within this minimal amount of search, and show that any other algorithm would have to search strictly more. The fraction of nodes needed to be searched approaches zero as the number of agents grows. If additional time remains, our anytime algorithm searches further, and establishes a progressively lower tight bound. Surprisingly, just searching one more node drops the bound in half. As desired, our algorithm lowers the bound rapidly early on, and exhibits diminishing returns to computation. It also significantly outperforms its obvious contenders. Finally, we show how to distribute the desired
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