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51
Truthful approximation mechanisms for restricted combinatorial auctions
, 2002
"... When attempting to design a truthful mechanism for a computationally hard problem such as combinatorial auctions, one is faced with the problem that most efficiently computable heuristics can not be embedded in any truthful mechanism (e.g. VCGlike payment rules will not ensure truthfulness). We dev ..."
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Cited by 126 (5 self)
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When attempting to design a truthful mechanism for a computationally hard problem such as combinatorial auctions, one is faced with the problem that most efficiently computable heuristics can not be embedded in any truthful mechanism (e.g. VCGlike payment rules will not ensure truthfulness). We develop a set of techniques that allow constructing efficiently computable truthful mechanisms for combinatorial auctions in the special case where each bidder desires a specific known subset of items and only the valuation is unknown by the mechanism (the single parameter case). For this case we extend the work of Lehmann O’Callaghan, and Shoham, who presented greedy heuristics. We show how to use IFTHENELSE constructs, perform a partial search, and use the LP relaxation. We apply these techniques for several canonical types of combinatorial auctions, obtaining truthful mechanisms with provable approximation ratios. 1
ApproximatelyStrategyproof and Tractable MultiUnit Auctions
, 2004
"... We present an approximatelyefficient and approximatelystrategyproof auction mechanism for a singlegood multiunit allocation problem. The bidding language allows marginaldecreasing piecewise constant curves and quantitybased side constraints. We develop a fully polynomialtime approximation sch ..."
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Cited by 61 (11 self)
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We present an approximatelyefficient and approximatelystrategyproof auction mechanism for a singlegood multiunit allocation problem. The bidding language allows marginaldecreasing piecewise constant curves and quantitybased side constraints. We develop a fully polynomialtime approximation scheme for the multiunit allocation problem, which computes a approximation in worstcase time , given bids each with a constant number of pieces. We integrate this approximation scheme within a VickreyClarke Groves mechanism and compute payments for an asymptotic cost of ! . The maximal possible gain from manipulation to a bidder in the combined scheme is bounded by 429416716 " is the total surplus in the efficient outcome.
Polynomial Time Approximation Schemes for ClassConstrained Packing Problems
 Proc. of Workshop on Approximation Algorithms
, 1999
"... . We consider variants of the classic bin packing and multiple knapsack problems, in which sets of items of different classes (colors) need to be placed in bins; the items may have different sizes and values. Each bin has a limited capacity, and a bound on the number of distinct classes of items ..."
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Cited by 33 (6 self)
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. We consider variants of the classic bin packing and multiple knapsack problems, in which sets of items of different classes (colors) need to be placed in bins; the items may have different sizes and values. Each bin has a limited capacity, and a bound on the number of distinct classes of items it can hold. In the classconstrained multiple knapsack (CCMK) problem, our goal is to maximize the total value of packed items, whereas in the classconstrained binpacking (CCBP), we seek to minimize the number of (identical) bins, needed for packing all the items. We give a polynomial time approximation scheme (PTAS) for CCMK and a dual PTAS for CCBP. We also show that the 01 classconstrained knapsack admits a fully polynomial time approximation scheme, even when the number of distinct colors of items depends on the input size. Finally, we introduce the generalized classconstrained packing problem (GCCP), where each item may have more than one color. We show that GCCP is APX...
Automating Enterprise Application Placement in Resource Utilities
, 2003
"... This paper presents an approach for automating such exercises. We characterize the complex time varying demands of such applications and then assign them to a small number of servers such that their capacity requirements are satis ed. The approach can be repeated on an ongoing basis to ensure ..."
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Cited by 25 (5 self)
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This paper presents an approach for automating such exercises. We characterize the complex time varying demands of such applications and then assign them to a small number of servers such that their capacity requirements are satis ed. The approach can be repeated on an ongoing basis to ensure the continued ecient use of resources. A case study using data from 41 data center servers is used to demonstrate the eectiveness of the technique
Combinatorial Auctions, Knapsack Problems, and Hillclimbing Search
 In Canadian Conference on AI
, 2001
"... . This paper examines the performance of hillclimbing algorithms on standard test problems for combinatorial auctions (CAs). On singleunit CAs, deterministic hillclimbers are found to perform well, and their performance can be improved significantly by randomizing them and restarting them sev ..."
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Cited by 21 (1 self)
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. This paper examines the performance of hillclimbing algorithms on standard test problems for combinatorial auctions (CAs). On singleunit CAs, deterministic hillclimbers are found to perform well, and their performance can be improved significantly by randomizing them and restarting them several times, or by using them collectively. For some problems this good performance is shown to be no better than chancel; on others it is due to a wellchosen scoring function. The paper draws attention to the fact that multiunit CAs have been studied widely under a different name: multidimensional knapsack problems (MDKP). On standard test problems for MDKP, one of the deterministic hillclimbers generates solutions that are on average 99% of the best known solutions. 1 Introduction Suppose there are three items for auction, X, Y, and Z, and three bidders, B1, B2, and B3. B1 wants any one of the items and will pay $5, B2 wants two items  X and one of Y or Z  and will pay $9, an...
On Preemptive Resource Constrained Scheduling: Polynomialtime Approximation Schemes
, 2002
"... We study resource constrained scheduling problems where the objective is to compute feasible preemptive schedules minimizing the makespan and using no more resources than what are available. ..."
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Cited by 18 (9 self)
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We study resource constrained scheduling problems where the objective is to compute feasible preemptive schedules minimizing the makespan and using no more resources than what are available.
A New Fully Polynomial Approximation Scheme for the Knapsack Problem
 Proceedings 1st International Workshop on Approximation Algorithms for Combinatorial Optimization
, 1998
"... A new fully polynomial approximation scheme (FPTAS) is presented for the classical 01 knapsack problem. It considerably improves the space requirements. The two best previously known approaches need O(n+1=" 3 ) and O(n \Delta 1=") space, respectively. Our new approximation scheme requ ..."
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Cited by 16 (1 self)
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A new fully polynomial approximation scheme (FPTAS) is presented for the classical 01 knapsack problem. It considerably improves the space requirements. The two best previously known approaches need O(n+1=" 3 ) and O(n \Delta 1=") space, respectively. Our new approximation scheme requires only O(n + 1=" 2 ) space while also reducing the running time. 1 Introduction The classical 01 knapsack problem (KP ) is defined by (KP ) maximize n X i=1 p i x i subject to n X i=1 w i x i c (1) x i 2 f0; 1g; i = 1; : : : ; n; with p i ; w i and c being positive integers. This special case of integer programming can be interpreted as filling a knapsack with a subset of items maximizing the profit in the knapsack such that its weight is not greater than the capacity c. A set of items will be called feasible if it fulfills (1), i.e. if its total weight is not greater than the given capacity. The optimal solution value will be denoted by z . An overview of all aspects of (KP ) an...
Optimal filtering of source address prefixes: Models and algorithms
 In Proceedings of IEEE Infocom
, 2009
"... Abstract — How can we protect the network infrastructure from malicious traffic, such as scanning, malicious code propagation, and distributed denialofservice (DDoS) attacks? One mechanism for blocking malicious traffic is filtering: access control lists (ACLs) can selectively block traffic based ..."
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Cited by 14 (2 self)
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Abstract — How can we protect the network infrastructure from malicious traffic, such as scanning, malicious code propagation, and distributed denialofservice (DDoS) attacks? One mechanism for blocking malicious traffic is filtering: access control lists (ACLs) can selectively block traffic based on fields of the IP header. Filters (ACLs) are already available in the routers today but are a scarce resource because they are stored in expensive ternary content addressable memory (TCAM). In this paper, we develop, for the first time, a framework for studying filter selection as a resource allocation problem. Within this framework, we study four practical cases of source address/prefix filtering, which correspond to different attack scenarios and operator’s policies. We show that filter selection optimization leads to novel variations of the multidimensional knapsack problem and we design optimal, yet computationally efficient, algorithms to solve them. We also evaluate our approach using data from Dshield.org and demonstrate that it brings significant benefits in practice. Our set of algorithms is a building block that can be immediately used by operators and manufacturers to block malicious traffic in a costefficient way. I.
Approximate Strong Separation with Application in Fractional Graph Coloring and Preemptive Scheduling
 IN PROCEEDINGS OF THE 19TH INTERNATIONAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE
, 2001
"... In this paper we show that approximation algorithms for the weighted independent set and sdimensional knapsack problem with ratio a can be turned into approximation algorithms with the same ratio for fractional weighted graph coloring and preemptive resource constrained scheduling. In order to o ..."
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Cited by 14 (2 self)
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In this paper we show that approximation algorithms for the weighted independent set and sdimensional knapsack problem with ratio a can be turned into approximation algorithms with the same ratio for fractional weighted graph coloring and preemptive resource constrained scheduling. In order to obtain these results, we generalize known results by Grötschel, Lovasz and Schrijver on separation, nonemptiness test, optimization and violation in the direction of approximability.
The distortion of cardinal preferences in voting
 In The Tenth International Workshop on Cooperative Information Agents (CIA 2006
, 2006
"... Abstract. The theoretical guarantees provided by voting have distinguished it as a prominent method of preference aggregation among autonomous agents. However, unlike humans, agents usually assign each candidate an exact utility, whereas an election is resolved based solely on each voter’s linear or ..."
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Cited by 12 (5 self)
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Abstract. The theoretical guarantees provided by voting have distinguished it as a prominent method of preference aggregation among autonomous agents. However, unlike humans, agents usually assign each candidate an exact utility, whereas an election is resolved based solely on each voter’s linear ordering of candidates. In essence, the agents ’ cardinal (utilitybased) preferences are embedded into the space of ordinal preferences. This often gives rise to a distortion in the preferences, and hence in the social welfare of the outcome. In this paper, we formally define and analyze the concept of distortion. We fully characterize the distortion under different restrictions imposed on agents’ cardinal preferences; both possibility and strong impossibility results are established. We also tackle some computational aspects of calculating the distortion. Ultimately, we argue that, whenever voting is applied in a multiagent system, distortion must be a pivotal consideration. 1