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Faster and simpler algorithms for multicommodity flow and other fractional packing problems
"... This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We present new faster and much simpler algorithms for these problems. ..."
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Cited by 325 (5 self)
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This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We present new faster and much simpler algorithms for these problems.
Polynomial time algorithms for multicast network code construction
 IEEE TRANS. ON INFO. THY
, 2005
"... The famous maxflow mincut theorem states that a source node can send information through a network ( ) to a sink node at a rate determined by the mincut separating and. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediat ..."
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Cited by 316 (29 self)
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The famous maxflow mincut theorem states that a source node can send information through a network ( ) to a sink node at a rate determined by the mincut separating and. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to reencode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures.
Admissible Heuristics for Optimal Planning
 IN PROCEEDINGS OF AIPS00
, 2000
"... hsp and hspr are two recent planners that search the statespace using an heuristic function extracted from Strips encodings. hsp does a forward search from the initial state recomputing the heuristic in every state, while hspr does a regression search from the goal computing a suitable representati ..."
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Cited by 195 (23 self)
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hsp and hspr are two recent planners that search the statespace using an heuristic function extracted from Strips encodings. hsp does a forward search from the initial state recomputing the heuristic in every state, while hspr does a regression search from the goal computing a suitable representation of the heuristic only once. Both planners have shown good performance, often producing solutions that are competitive in time and number of actions with the solutions found by Graphplan and sat planners. hsp and hspr, however, are not optimal planners. This is because the heuristic function is not admissible and the search algorithms are not optimal. In this paper we address this problem. We formulate a new admissible heuristic for planning, use it to guide an ida search, and empirically evaluate the resulting optimal planner over a number of domains. The main contribution is the idea underlying the heuristic that yields not one but a whole family of polynomial and admissible heuristics that trade accuracy for efficiency. The formulation is general and sheds some light on the heuristics used in hsp and Graphplan, and their relation. It exploits the factored (Strips) representation of planning problems, mapping shortestpath problems in statespace into suitably defined shortestpath problems in atomspace. The formulation applies with little variation to sequential and parallel planning, and problems with different action costs.
An Efficient Implementation Of A Scaling MinimumCost Flow Algorithm
 Journal of Algorithms
, 1992
"... . The scaling pushrelabel method is an important theoretical development in the area of minimumcost flow algorithms. We study practical implementations of this method. We are especially interested in heuristics which improve reallife performance of the method. Our implementation works very well o ..."
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Cited by 138 (6 self)
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. The scaling pushrelabel method is an important theoretical development in the area of minimumcost flow algorithms. We study practical implementations of this method. We are especially interested in heuristics which improve reallife performance of the method. Our implementation works very well over a wide range of problem classes. In our experiments, it was always competitive with the established codes, and usually outperformed these codes by a wide margin. Some heuristics we develop may apply to other network algorithms. Our experimental work on the minimumcost flow problem motivated theoretical work on related problems. Supported in part by ONR Young Investigator Award N0001491J1855, NSF Presidential Young Investigator Grant CCR8858097 with matching funds from AT&T and DEC, Stanford University Office of Technology Licensing, and a grant form the Powell Foundation. 1 1. Introduction. Significant theoretical progress has been made recently in the area of minimumcost flow ...
Polynomial Time Algorithms for Network Information Flow
 in 15th ACM Symposium on Parallel Algorithms and Architectures
, 2003
"... The famous maxflow mincut theorem states that a source node s can send information through a network (V; E) to a sink node t at a data rate determined by the mincut separating s and t. Recently it has been shown that this rate can also be achieved for multicasting to several sinks provided that t ..."
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Cited by 122 (1 self)
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The famous maxflow mincut theorem states that a source node s can send information through a network (V; E) to a sink node t at a data rate determined by the mincut separating s and t. Recently it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to reencode the information they receive. In contrast, we present graphs where without coding the rate must be a factor jV j) smaller. However, so far no fast algorithms for constructing appropriate coding schemes were known. Our main result are polynomial time algorithms for constructing coding schemes for multicasting at the maximal data rate.
Decoding ErrorCorrecting Codes via Linear Programming
, 2003
"... Errorcorrecting codes are fundamental tools used to transmit digital information over unreliable channels. Their study goes back to the work of Hamming [Ham50] and Shannon [Sha48], who used them as the basis for the field of information theory. The problem of decoding the original information up ..."
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Cited by 115 (5 self)
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Errorcorrecting codes are fundamental tools used to transmit digital information over unreliable channels. Their study goes back to the work of Hamming [Ham50] and Shannon [Sha48], who used them as the basis for the field of information theory. The problem of decoding the original information up to the full errorcorrecting potential of the system is often very complex, especially for modern codes that approach the theoretical limits of the communication channel. In this thesis we investigate the application of linear programming (LP) relaxation to the problem of decoding an errorcorrecting code. Linear programming relaxation is a standard technique in approximation algorithms and operations research, and is central to the study of efficient algorithms to find good (albeit suboptimal) solutions to very difficult optimization problems. Our new “LP decoders” have tight combinatorial characterizations of decoding success that can be used to analyze errorcorrecting performance. Furthermore, LP decoders have the desirable (and rare) property that whenever they output a result, it is guaranteed to be the optimal result: the most likely (ML) information sent over the
Auction algorithms for network flow problems: A tutorial introduction
 Comput. Optim. Appl
, 1992
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Achieving NearOptimal Traffic Engineering Solutions for Current OSPF/ISIS Networks
 IEEE/ACM Transactions on Networking
, 2002
"... Traffic engineering is aimed at distributing traffic so as to "optimize" a given performance criterion. The ability to carry out such an optimal distribution depends on both the routing protocol and the forwarding mechanisms in use in the network. In IP networks running the OSPF or ISIS p ..."
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Cited by 107 (4 self)
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Traffic engineering is aimed at distributing traffic so as to "optimize" a given performance criterion. The ability to carry out such an optimal distribution depends on both the routing protocol and the forwarding mechanisms in use in the network. In IP networks running the OSPF or ISIS protocols, routing is over shortest paths, and forwarding mechanisms are constrained to distributing traffic uniformly over equal cost shortest paths. These constraints often make achieving an optimal distribution of traffic impossible. In this paper, we propose and evaluate an approach, based on manipulating the set of next hops for routing prefixes, that is capable of realizing near optimal traffic distribution without any change to existing routing protocols and forwarding mechanisms. In addition, we explore the tradeoff that exists between performance and the overhead associated with the additional configuration steps that our solution requires. The paper's contributions are in formulating and evaluating an approach to traffic engineering for existing IP networks that achieves performance levels comparable to that offered when deploying other forwarding technologies such as MPLS.
An efficient earth mover’s distance algorithm for robust histogram comparison
 PAMI
, 2007
"... DRAFT We propose EMDL1: a fast and exact algorithm for computing the Earth Mover’s Distance (EMD) between a pair of histograms. The efficiency of the new algorithm enables its application to problems that were previously prohibitive due to high time complexities. The proposed EMDL1 significantly s ..."
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Cited by 96 (5 self)
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DRAFT We propose EMDL1: a fast and exact algorithm for computing the Earth Mover’s Distance (EMD) between a pair of histograms. The efficiency of the new algorithm enables its application to problems that were previously prohibitive due to high time complexities. The proposed EMDL1 significantly simplifies the original linear programming formulation of EMD. Exploiting the L1 metric structure, the number of unknown variables in EMDL1 is reduced to O(N) from O(N 2) of the original EMD for a histogram with N bins. In addition, the number of constraints is reduced by half and the objective function of the linear program is simplified. Formally without any approximation, we prove that the EMDL1 formulation is equivalent to the original EMD with a L1 ground distance. To perform the EMDL1 computation, we propose an efficient treebased algorithm, TreeEMD. TreeEMD exploits the fact that a basic feasible solution of the simplex algorithmbased solver forms a spanning tree when we interpret EMDL1 as a network flow optimization problem. We empirically show that this new algorithm has average time complexity of O(N 2), which significantly improves the best reported supercubic complexity of the original EMD. The accuracy of the proposed methods is evaluated by