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76
Modeling sensor networks
, 2008
"... In order to develop algorithms for sensor networks and in order to give mathematical correctness and performance proofs, models for various aspects of sensor networks are needed. This chapter presents and discusses currently used models for sensor networks. Generally, finding good models is a challe ..."
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Cited by 41 (5 self)
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In order to develop algorithms for sensor networks and in order to give mathematical correctness and performance proofs, models for various aspects of sensor networks are needed. This chapter presents and discusses currently used models for sensor networks. Generally, finding good models is a challenging task. On the one hand, a
Local approximation schemes for ad hoc and sensor networks
 In Proc. 3rd Joint Workshop on Foundations of Mobile Computing (DialMPOMC
, 2005
"... We present two local approaches that yield polynomialtime approximation schemes (PTAS) for the Maximum Independent Set and Minimum Dominating Set problem in unit disk graphs. The algorithms run locally in each node and compute a (1 + ε)approximation to the problems at hand for any given ε> 0. ..."
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Cited by 38 (9 self)
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We present two local approaches that yield polynomialtime approximation schemes (PTAS) for the Maximum Independent Set and Minimum Dominating Set problem in unit disk graphs. The algorithms run locally in each node and compute a (1 + ε)approximation to the problems at hand for any given ε> 0. The time complexity of both algorithms is O(TMIS + log ∗n/εO(1)), where TMIS is the time required to compute a maximal independent set in the graph, and n denotes the number of nodes. We then extend these results to a more general class of graphs in which the maximum number of pairwise independent nodes in every rneighborhood is at most polynomial in r. Such graphs of polynomially bounded growth are introduced as a more realistic model for wireless networks and they generalize existing models, such as unit disk graphs or coverage area graphs.
Leveraging Linial’s Locality Limit
"... www.dcg.ethz.ch Abstract. In this paper we extend the lower bound technique by Linial for local coloring and maximal independent sets. We show that constant approximations to maximum independent sets on a ring require at least logstar time. More generally, the product of approximation quality and r ..."
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Cited by 27 (8 self)
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www.dcg.ethz.ch Abstract. In this paper we extend the lower bound technique by Linial for local coloring and maximal independent sets. We show that constant approximations to maximum independent sets on a ring require at least logstar time. More generally, the product of approximation quality and running time cannot be less than logstar. Using a generalized ring topology, we gain identical lower bounds for approximations to minimum dominating sets. Since our generalized ring topology is contained in a number of geometric graphs such as the unit disk graph, our bounds directly apply as lower bounds for quite a few algorithmic problems in wireless networking. Having in mind these and other results about local approximations of maximum independent sets and minimum dominating sets, one might think that the former are always at least as difficult to obtain as the latter. Conversely, we show that graphs exist, where a maximum independent set can be determined without any communication, while finding even an approximation to a minimum dominating set is as hard as in general graphs. 1
Distributed approximate matching
, 2007
"... We consider distributed algorithms for approximate maximum matching on general graphs. Our main result is a randomized (4 + ɛ)approximation distributed algorithm for weighted maximum matching, whose running time is O(log n) for any constant ɛ> 0, where n is the number of nodes in the graph. In a ..."
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Cited by 21 (2 self)
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We consider distributed algorithms for approximate maximum matching on general graphs. Our main result is a randomized (4 + ɛ)approximation distributed algorithm for weighted maximum matching, whose running time is O(log n) for any constant ɛ> 0, where n is the number of nodes in the graph. In addition, we consider the dynamic case, where nodes are inserted and deleted one at a time. For unweighted dynamic graphs, we give an algorithm that maintains a (1 + ɛ)approximation in O(1/ɛ) time for each node insertion or deletion. For weighted dynamic graphs we give a constantfactor approximation algorithm that runs in constant time for each insertion or deletion.
FaultTolerant Clustering in Ad Hoc and Sensor Networks
 In 26th International Conference on Distributed Computing Systems (ICDCS
, 2006
"... In this paper, we study distributed approximation algorithms for faulttolerant clustering in wireless ad hoc and sensor networks. A kfold dominating set of a graph G =(V,E) is a subset S of V such that every node v ∈ V \ S has at least k neighbors in S. We study the problem in two network models. ..."
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Cited by 17 (1 self)
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In this paper, we study distributed approximation algorithms for faulttolerant clustering in wireless ad hoc and sensor networks. A kfold dominating set of a graph G =(V,E) is a subset S of V such that every node v ∈ V \ S has at least k neighbors in S. We study the problem in two network models. In general graphs, for arbitrary parameter t, we propose a distributed algorithm that runs in time O(t 2) and achieves an approximation ratio of O(t ∆ 2/t log ∆), wheren and ∆ denote the number of nodes in the network and the maximal degree, respectively. When the network is modeled as a unit disk graph, we give a probabilistic algorithm that runs in time O(log log n) and achieves an O(1) approximation in expectation. Both algorithms require only small messages of size O(log n) bits. 1
Improved Distributed Approximate Matching
"... We present improved algorithms for finding approximately optimal matchings in both weighted and unweighted graphs. For unweighted graphs, we give an algorithm providing (1 − ɛ)approximation in O(log n) time for any constant ɛ> 0. This result improves on the classical 1approximation due 2 to Isr ..."
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Cited by 16 (3 self)
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We present improved algorithms for finding approximately optimal matchings in both weighted and unweighted graphs. For unweighted graphs, we give an algorithm providing (1 − ɛ)approximation in O(log n) time for any constant ɛ> 0. This result improves on the classical 1approximation due 2 to Israeli and Itai. As a byproduct, we also provide an improved algorithm for unweighted matchings in bipartite graphs. In the context of weighted graphs, we give another algorithm which provides ( 1 − ɛ) approximation in general 2 graphs in O(log n) time. The latter result improves on the − ɛ)approximation in O(log n) time. known ( 1 4
Almost stable matchings by truncating the Gale–Shapley algorithm
 Algorithmica
, 2010
"... We show that the ratio of matched individuals to blocking pairs grows linearly with the number of propose–accept rounds executed by the Gale–Shapley algorithm for the stable marriage problem. Consequently, the participants can arrive at an almost stable matching even without full information about ..."
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Cited by 16 (5 self)
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We show that the ratio of matched individuals to blocking pairs grows linearly with the number of propose–accept rounds executed by the Gale–Shapley algorithm for the stable marriage problem. Consequently, the participants can arrive at an almost stable matching even without full information about the problem instance; for each participant, knowing only its local neighbourhood is enough. In distributedsystems parlance, this means that if each person has only a constant number of acceptable partners, an almost stable matching emerges after a constant number of synchronous communication rounds. We apply our results to give a distributed (2 + )approximation algorithm for maximumweight matching in bicoloured graphs and a centralised randomised constanttime approximation scheme for estimating the size of a stable matching. 1
Networks Cannot Compute Their Diameter in Sublinear Time preliminary version please check for updates
, 2011
"... We study the problem of computing the diameter of a network in a distributed way. The model of distributed computation we consider is: in each synchronous round, each node can transmit a different (but short) message to each of its neighbors. We provide an ˜ Ω(n) lower bound for the number of commun ..."
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Cited by 14 (2 self)
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We study the problem of computing the diameter of a network in a distributed way. The model of distributed computation we consider is: in each synchronous round, each node can transmit a different (but short) message to each of its neighbors. We provide an ˜ Ω(n) lower bound for the number of communication rounds needed, where n denotes the number of nodes in the network. This lower bound is valid even if the diameter of the network is a small constant. We also show that a (3/2 − ε)approximation of the diameter requires ˜ Ω ( √ n) rounds. Furthermore we use our new technique to prove an ˜ Ω ( √ n) lower bound on approximating the girth of a graph by a factor 2 − ε. Contact author:
T.: Distributed approximation of capacitated dominating sets
 In: Proc. 19th Annual ACM Symposium on Parallel Algorithms and Architectures (SPAA
, 2007
"... We study local, distributed algorithms for the capacitated minimum dominating set (CapMDS) problem, which arises in various distributed network applications. Given a network graph G = (V, E), and a capacity cap(v) ∈ N for each node v ∈ V, the CapMDS problem asks for a subset S ⊆ V of minimal cardin ..."
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Cited by 14 (1 self)
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We study local, distributed algorithms for the capacitated minimum dominating set (CapMDS) problem, which arises in various distributed network applications. Given a network graph G = (V, E), and a capacity cap(v) ∈ N for each node v ∈ V, the CapMDS problem asks for a subset S ⊆ V of minimal cardinality, such that every network node not in S is covered by at least one neighbor in S, and every node v ∈ S covers at most cap(v) of its neighbors. We prove that in general graphs and even with uniform capacities, the problem is inherently nonlocal, i.e., every distributed algorithm achieving a nontrivial approximation ratio must have a time complexity that essentially grows linearly with the network diameter. On the other hand, if for some parameter ɛ> 0, capacities can be violated by a factor of 1 + ɛ, CapMDS becomes much more local. Particularly, based on a novel distributed randomized rounding technique, we present a distributed bicriteria algorithm that achieves an O(log ∆)approximation in time O(log 3 n + log(n)/ɛ), where n and ∆ denote the number of nodes and the maximal degree in G, respectively. Finally, we prove that in geometric network graphs typically arising in wireless settings, the uniform problem can be approximated within a constant factor in logarithmic time, whereas the nonuniform problem remains entirely nonlocal.
A local 2approximation algorithm for the vertex cover problem
 IN PROC. 23RD SYMPOSIUM ON DISTRIBUTED COMPUTING (DISC 2009), VOLUME 5805 OF LNCS
, 2009
"... We present a distributed 2approximation algorithm for the minimum vertex cover problem. The algorithm is deterministic, and it runs in (∆ + 1)² synchronous communication rounds, where ∆ is the maximum degree of the graph. For ∆ = 3, we give a 2approximation algorithm also for the weighted version ..."
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Cited by 13 (11 self)
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We present a distributed 2approximation algorithm for the minimum vertex cover problem. The algorithm is deterministic, and it runs in (∆ + 1)² synchronous communication rounds, where ∆ is the maximum degree of the graph. For ∆ = 3, we give a 2approximation algorithm also for the weighted version of the problem.