Results 11  20
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104
Expected Data Rate: An Accurate HighThroughput Path Metric For MultiHop Wireless Routing
, 2005
"... We present a new metric, Expected Data Rate (EDR), for accurately finding highthroughput paths in multihop ad hoc wireless networks. Our metric is based upon a new model for transmission interference which is a critical factor in determining path throughput. We construct a realistic and practical ..."
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Cited by 22 (2 self)
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We present a new metric, Expected Data Rate (EDR), for accurately finding highthroughput paths in multihop ad hoc wireless networks. Our metric is based upon a new model for transmission interference which is a critical factor in determining path throughput. We construct a realistic and practical transmission interference model by (1) determining transmission contention degree of each link as a function of the wireless link loss, (2) quantifying the impact of the wireless link loss on medium access backoff, and (3) considering possible concurrent transmissions when two links do not interfere with each other. Our transmission interference model also takes the nonoptimality of IEEE 802.11 medium access scheduling into account. Using extensive ns2 simulations of IEEE 802.11 ad hoc networks, we find that EDR can accurately determine the achievable data rates of ad hoc paths, thereby significantly outperforming the other existing metrics.
Approximation Algorithms for Maximum Independent Set of PseudoDisks
, 2008
"... We present approximation algorithms for maximum independent set of pseudodisks in the plane, both in the weighted and unweighted cases. For the unweighted case, we prove that a local search algorithm yields a PTAS. For the weighted case, we suggest a novel rounding scheme based on an LP relaxation ..."
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Cited by 22 (4 self)
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We present approximation algorithms for maximum independent set of pseudodisks in the plane, both in the weighted and unweighted cases. For the unweighted case, we prove that a local search algorithm yields a PTAS. For the weighted case, we suggest a novel rounding scheme based on an LP relaxation of the problem, that leads to a constantfactor approximation. Most previous algorithms for maximum independent set (in geometric settings) relied on packing arguments that are not applicable in this case. As such, the analysis of both algorithms requires some new combinatorial ideas, which we believe to be of independent interest.
Geometric clustering to minimize the sum of cluster sizes
 In Proc. 13th European Symp. Algorithms, Vol 3669 of LNCS
, 2005
"... Abstract. We study geometric versions of the minsize kclustering problem, a clustering problem which generalizes clustering to minimize the sum of cluster radii and has important applications. We prove that the problem can be solved in polynomial time when the points to be clustered are located on ..."
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Cited by 21 (0 self)
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Abstract. We study geometric versions of the minsize kclustering problem, a clustering problem which generalizes clustering to minimize the sum of cluster radii and has important applications. We prove that the problem can be solved in polynomial time when the points to be clustered are located on a line. For Euclidean spaces of higher dimensions, we show that the problem is NPhard and present polynomial time approximation schemes. The latter result yields an improved approximation algorithm for the related problem of kclustering to minimize the sum of cluster diameters. 1
Distributed Algorithms for Approximating Wireless Network Capacity
"... Abstract—In this paper we consider the problem of maximizing wireless network capacity (a.k.a. oneshot scheduling) in both the protocol and physical models. We give the first distributed algorithms with provable guarantees in the physical model, and show how they can be generalized to more complica ..."
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Cited by 20 (2 self)
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Abstract—In this paper we consider the problem of maximizing wireless network capacity (a.k.a. oneshot scheduling) in both the protocol and physical models. We give the first distributed algorithms with provable guarantees in the physical model, and show how they can be generalized to more complicated metrics and settings in which the physical assumptions are slightly violated. We also give the first algorithms in the protocol model that do not assume transmitters can coordinate with their neighbors in the interference graph, so every transmitter chooses whether to broadcast based purely on local events. Our techniques draw heavily from algorithmic game theory and machine learning theory, even though our goal is a distributed algorithm. Indeed, our main results allow every transmitter to run any algorithm it wants, so long as its algorithm has a learningtheoretic property known as noregret in a gametheoretic setting. I.
Discrete mathematics and radio channel assignment
 IN “RECENT ADVANCES IN THEORETICAL AND APPLIED DISCRETE MATHEMATICS
, 2001
"... The radio channel assignment problem has recently sparked off much research in discrete applied mathematics, based on models that extend the idea of graph colouring. This is the subject of the present chapter. ..."
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Cited by 20 (0 self)
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The radio channel assignment problem has recently sparked off much research in discrete applied mathematics, based on models that extend the idea of graph colouring. This is the subject of the present chapter.
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 19 (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.
Optimization problems in multipleinterval graphs
 In Proceedings of the 18th annual Symposium On Discrete Algorithms (SODA
, 2007
"... Multipleinterval graphs are a natural generalization of interval graphs where each vertex may have more then one interval associated with it. We initiate the study of optimization problems in multipleinterval graphs by considering three classical problems: Minimum Vertex Cover, Minimum Dominating ..."
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Cited by 18 (5 self)
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Multipleinterval graphs are a natural generalization of interval graphs where each vertex may have more then one interval associated with it. We initiate the study of optimization problems in multipleinterval graphs by considering three classical problems: Minimum Vertex Cover, Minimum Dominating Set, and Maximum Clique. We describe applications for each one of these problems, and then proceed to discuss approximation algorithms for them. Our results can be summarized as follows: Let t be the number of intervals associated with each vertex in a given multipleinterval graph. For Minimum Vertex Cover, we give a (2 − 1/t)approximation algorithm which also works when a tinterval representation of our given graph is absent. Following this, we give a t 2approximation algorithm for Minimum Dominating Set which adapts well to more general variants of the problem. We then proceed to prove that Maximum Clique is NPhard already for 3interval graphs, and provide a (t 2 −t+ 1)/2approximation algorithm for general values of t ≥ 2, using bounds proven for the socalled transversal number of tinterval families.
A robust ptas for maximum weight independent sets in unit disk graphs
 In WG
, 2004
"... Abstract. A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a polynomialtime approximation scheme for the maximum weight independent set problem in unit disk graphs. In contrast to previously known approximation schemes, our approach does not require a geo ..."
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Cited by 18 (0 self)
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Abstract. A unit disk graph is the intersection graph of unit disks in the euclidean plane. We present a polynomialtime approximation scheme for the maximum weight independent set problem in unit disk graphs. In contrast to previously known approximation schemes, our approach does not require a geometric representation (specifying the coordinates of the disk centers). The approximation algorithm presented is robust in the sense that it accepts any graph as input and either returns a (1 + ε)approximate independent set or a certificate showing that the input graph is no unit disk graph. The algorithm can easily be extended to other families of intersection graphs of geometric objects. 1
Independent set of intersection graphs of convex objects in 2D
 in 2D. Comput. Geometry: Theory & Appls
, 2004
"... Abstract. The intersection graph of a set of geometric objects is defined as agraph G = (S; E) in which there is an edge between two nodes si; sj 2 S if si " sj 6 =;. The problem of computing a maximum independent set in the intersection graph of a set of objects is known to be NPcomplete ..."
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Cited by 18 (1 self)
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Abstract. The intersection graph of a set of geometric objects is defined as agraph G = (S; E) in which there is an edge between two nodes si; sj 2 S if si &quot; sj 6 =;. The problem of computing a maximum independent set in the intersection graph of a set of objects is known to be NPcomplete for most casesin two and higher dimensions. We present approximation algorithms for computing a maximum independent set of intersection graphs of convex objects in R 2. Specifically, given a set of n line segments in the plane with maximum independent set of size ^, we present algorithms that find an independent set of size atleast ( i) (^=2 log(2n=^)) 1=2 in time O(n
Enhancing Cellular Multicast Performance Using Ad Hoc Networks
, 2005
"... Although multicast communication is wellsuited to shared wireless links, receiver heterogeneity impedes the use of multicast in wireless networks. In this paper, we examine an approach that addresses the receiver heterogeneity problem in cellular multicast with the help of an additional IEEE 802.1 ..."
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Cited by 17 (2 self)
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Although multicast communication is wellsuited to shared wireless links, receiver heterogeneity impedes the use of multicast in wireless networks. In this paper, we examine an approach that addresses the receiver heterogeneity problem in cellular multicast with the help of an additional IEEE 802.11 ad hoc network. The basic idea is to allow the cellular receivers experiencing poor channel conditions to use the ad hoc network to connect to those cellular receivers that are experiencing good cellular channel conditions. The good receivers (called proxies) relay multicast data to the poor receivers through the ad hoc network. We specifically consider the third generation cellular high data rate (HDR) Broadcast/Multicast Services (BCMCS). We develop a new routing algorithm to find efficient ad hoc paths from the proxies to the cellular multicast receivers. Unlike existing algorithms [1], our routing algorithm considers the effect of ad hoc path interference. Using simulations of an HDR BCMCS network in conjunction with an IEEE ad hoc network, we show that our algorithm improves the receiver goodput by up to 280% compared to that obtained without using ad hoc paths. We also show that our algorithm achieves up to 98 % higher receiver goodput in comparison to the greedy algorithm proposed in [1].