Results 1  10
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25
Constanttime distributed scheduling policies for ad hoc wireless networks
 in Proceedings of IEEE Conference on Decision and Control
, 2006
"... Abstract — We propose two new distributed scheduling policies for ad hoc wireless networks that can achieve provable capacity regions. Known scheduling policies that guarantee comparable capacity regions are either centralized or need computation time that increases with the size of the network. In ..."
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Cited by 48 (5 self)
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Abstract — We propose two new distributed scheduling policies for ad hoc wireless networks that can achieve provable capacity regions. Known scheduling policies that guarantee comparable capacity regions are either centralized or need computation time that increases with the size of the network. In contrast, the unique feature of the proposed distributed scheduling policies is that they are constanttime policies, i.e., the time needed for computing a schedule is independent of the network size. Hence, they can be easily deployed in large networks. I.
A Distributed Joint ChannelAssignment, Scheduling and Routing Algorithm for MultiChannel Ad Hoc Wireless Networks
 In Proceedings of IEEE INFOCOM
, 2007
"... Abstract — The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple nonoverlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the ..."
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Cited by 37 (0 self)
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Abstract — The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple nonoverlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the increased bandwidth in multichannel multiradio ad hoc networks. In this paper, we develop a fully distributed algorithm that jointly solves the channelassignment, scheduling and routing problem. Our algorithm is an online algorithm, i.e., it does not require prior information on the offered load to the network, and can adapt automatically to the changes in the network topology and offered load. We show that our algorithm is provably efficient. That is, even compared with the optimal centralized and offline algorithm, our proposed distributed algorithm can achieve a provable fraction of the maximum system capacity. Further, the achievable fraction that we can guarantee is larger than that of some other comparable algorithms in the literature. I.
Distributed Weighted Matching
 In 18th DISC (Amsterdam, the Netherlands, 2004), R. Guerraoui (Ed.), LNCS 3274
, 2003
"... In this paper, we present fast and fully distributed algorithms for matching in weighted trees and general weighted graphs. The time complexity as well as the approximation ratio of the tree algorithm is constant. In particular, the approximation ratio is 4. For the general graph algorithm we pro ..."
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Cited by 28 (2 self)
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In this paper, we present fast and fully distributed algorithms for matching in weighted trees and general weighted graphs. The time complexity as well as the approximation ratio of the tree algorithm is constant. In particular, the approximation ratio is 4. For the general graph algorithm we prove a constant ratio bound of 5 and a polylogarithmic time complexity of O(log n).
A fast distributed algorithm for approximating the maximum matching
 Discrete Applied Mathematics, Volume 143, Issues
, 2004
"... Abstract. We present a distributed approximation algorithm that computes in every graph G a matching M of size at least 2 β(G), where 3 β(G) is the size of a maximum matching in G. The algorithm runs in O(log 4 V (G)) rounds in the synchronous, message passing model of computation and matches the ..."
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Cited by 17 (3 self)
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Abstract. We present a distributed approximation algorithm that computes in every graph G a matching M of size at least 2 β(G), where 3 β(G) is the size of a maximum matching in G. The algorithm runs in O(log 4 V (G)) rounds in the synchronous, message passing model of computation and matches the best known asymptotic complexity for computing a maximal matching in the same protocol. This improves the running time of an algorithm proposed recently by the authors in [2]. 1
Complexity in wireless scheduling: Impact and tradeoffs
 in Proceedings of ACM Mobihoc, Hong Kong
, 2008
"... It has been an important research topic since 1992 to maximize stability region in constrained queueing systems, which includes the study of scheduling over wireless ad hoc networks. In this paper, we propose a framework to study a wide range of existing and future scheduling algorithms and characte ..."
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Cited by 12 (6 self)
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It has been an important research topic since 1992 to maximize stability region in constrained queueing systems, which includes the study of scheduling over wireless ad hoc networks. In this paper, we propose a framework to study a wide range of existing and future scheduling algorithms and characterize the achieved tradeoffs in stability, delay, and complexity. These characterizations reveal interesting properties hidden in the study of any one or two dimensions in isolation. For example, decreasing complexity from exponential to polynomial, while keeping stability region the same, generally comes at the expense of exponential growth of delays. Investigating tradeoffs in the 3dimensional space allows a designer to fix one dimension and vary the other two jointly. For example, incentives for using scheduling algorithms with only partial throughputguarantee can be quantified with regards to delay and complexity. Tradeoff analysis is then extended to systems with congestion control through utility maximization for nonstabilizable arrival inputs, where the complexityutilitydelay tradeoff is shown to be different from the complexitystabilitydelay tradeoff. Finally, we analyze more practical models with bounded message size, and consider “effective throughput” which reflects resource occupied by control messages. We show that effective throughput may degrade significantly in certain scheduling algorithms, and suggest a mechanism to avoid this problem in light of the 3D tradeoff framework.
A Faster Distributed Algorithm for Computing Maximal Matchings Deterministically (Extended Abstract)
, 1999
"... ) Micha/l Ha'n'ckowiak Dept of Math and CS Adam Mickiewicz University Pozna'n, Poland Micha/l Karo'nski Dept of Math and CS Adam Mickiewicz University Pozna'n, Poland & Dept of Math and CS Emory University Atlanta, Georgia, USA Alessandro Panconesi Dept of CS University of Bologna Bo ..."
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Cited by 10 (2 self)
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) Micha/l Ha'n'ckowiak Dept of Math and CS Adam Mickiewicz University Pozna'n, Poland Micha/l Karo'nski Dept of Math and CS Adam Mickiewicz University Pozna'n, Poland & Dept of Math and CS Emory University Atlanta, Georgia, USA Alessandro Panconesi Dept of CS University of Bologna Bologna, Italy Abstract We show that maximal matchings can be computed deterministically in O(log 4 n) rounds in the synchronous, messagepassing model of computation. This improves on an earlier result by three logfactors. 1 Introduction In this paper we show that maximal matchings (MM's) can be computed deterministically in O(log 4 n) rounds in the synchronous, messagepassing model of computation. This improves substantially on an earlier result by the present authors, which shows that MM's can be computed in O(log 7 n) many rounds [9]. This rather substantial improvement in asymptotics is based on several new algorithmic ideas that, we hope, might prove useful in other conte...
Distributed and Parallel Algorithms for Weighted Vertex Cover . . .
, 2009
"... The paper presents distributed and parallel δapproximation algorithms for covering problems, where δ is the maximum number of variables on which any constraint depends (for example, δ = 2 for vertex cover). Specific results include the following. • For weighted vertex cover, the first distributed 2 ..."
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Cited by 9 (3 self)
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The paper presents distributed and parallel δapproximation algorithms for covering problems, where δ is the maximum number of variables on which any constraint depends (for example, δ = 2 for vertex cover). Specific results include the following. • For weighted vertex cover, the first distributed 2approximation algorithm taking O(log n) rounds and the first parallel 2approximation algorithm in RNC. The algorithms generalize to covering mixed integer linear programs (CMIP) with two variables per constraint (δ = 2). • For any covering problem with monotone constraints and submodular cost, a distributed δapproximation algorithm taking O(log² C) rounds, where C is the number of constraints. (Special cases include CMIP, facility location, and probabilistic (twostage) variants of these problems.)
Distributed Weighted Vertex Cover via Maximal Matchings
, 2004
"... In this paper we consider the problem of computing a minimumweight vertexcover in an nnode, weighted, undirected graph G = (V,E). We present a fully distributed algorithm for computing vertex covers of weight at most twice the optimum, in the case of integer weights. Our algorithm runs in an expe ..."
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Cited by 8 (1 self)
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In this paper we consider the problem of computing a minimumweight vertexcover in an nnode, weighted, undirected graph G = (V,E). We present a fully distributed algorithm for computing vertex covers of weight at most twice the optimum, in the case of integer weights. Our algorithm runs in an expected number of O(logn + log ˆW) communication rounds, where ˆW is the average vertexweight. The previous best algorithm for this problem requires O(logn(log n + log ˆW)) rounds and it is not fully distributed. For a maximal matching M in G it is a wellknown fact that any vertexcover in G needs to have at least M  vertices. Our algorithm is based on a generalization of this combinatorial lowerbound to the weighted setting.
A local 2approximation algorithm for the vertex cover problem
 In Proc. 23rd Symposium on Distributed Computing (DISC 2009), volume 5805 of LNCS
, 2009
"... Abstract. 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 weig ..."
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Cited by 6 (5 self)
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Abstract. 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. 1