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45
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 81 (9 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 75 (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.
Performance of Random Access Scheduling Schemes in Multihop Wireless Networks
"... The scheduling problem in multihop wireless networks has been extensively investigated. Although throughput optimal scheduling solutions have been developed in the literature, they are unsuitable for multihop wireless systems because they are usually centralized and have very high complexity. In ..."
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Cited by 73 (7 self)
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The scheduling problem in multihop wireless networks has been extensively investigated. Although throughput optimal scheduling solutions have been developed in the literature, they are unsuitable for multihop wireless systems because they are usually centralized and have very high complexity. In this paper, we develop a randomaccess based scheduling scheme that utilizes local information. The important features of this scheme include constanttime complexity, distributed operations, and a provable performance guarantee. Analytical results show that it guarantees a larger fraction of the optimal throughput performance than the stateoftheart. Through simulations with both singlehop and multihop traffics, we observe that the scheme provides high throughput, close to that of a wellknown highlyefficient centralized greedy solution called the Greedy Maximal Scheduler.
Distributed weighted matching
 Lecture Notes in Computer Science
"... In this paper, we present fast distributed approximation 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. For the general graph algorithm we prove a constant ratio bound and a polylogarit ..."
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Cited by 42 (2 self)
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In this paper, we present fast distributed approximation 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. For the general graph algorithm we prove a constant ratio bound and a polylogarithmic time complexity of O(log2 n).
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 22 (9 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.
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 18 (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
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
Local Distributed Decision
 In FOCS 2011
"... A central theme in distributed network algorithms concerns understanding and coping with the issue of locality. Despite considerable progress, research efforts in this direction have not yet resulted in a solid basis in the form of a fundamental computational complexity theory for locality. Inspired ..."
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Cited by 17 (11 self)
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A central theme in distributed network algorithms concerns understanding and coping with the issue of locality. Despite considerable progress, research efforts in this direction have not yet resulted in a solid basis in the form of a fundamental computational complexity theory for locality. Inspired by sequential complexity theory, we focus on a complexity theory for distributed decision problems. In the context of locality, solving a decision problem requires the processors to independently inspect their local neighborhoods and then collectively decide whether a given global input instance belongs to some specified language. We consider the standard LOCAL model of computation and define LD(t) (for local decision) as the class of decision problems that can be solved in t communication rounds. We first study the intriguing question of whether randomization helps in local distributed computing, and to what extent. Specifically, we define the corresponding randomized class BPLD(t, p, q), containing all languages for which there exists a randomized algorithm that runs in t rounds, accepts correct instances with probability at least p and rejects incorrect ones with probability at least q. We show that p 2 +q = 1 is a threshold for the containment of LD(t) in BPLD(t, p, q). More precisely, we show that there exists a language that does not belong to LD(t) for any t = o(n) but does belong to BPLD(0, p, q) for any p, q ∈ (0, 1] such that p 2 +q ≤ 1. On the other hand, we show that, restricted to
The Locality of Distributed Symmetry Breaking
"... We present new bounds on the locality of several classical symmetry breaking tasks in distributed networks. A sampling of the results include 1) A randomized algorithm for computing a maximal matching (MM) in O(log ∆+(log log n) 4) rounds, where ∆ is the maximum degree. This improves a 25year old ..."
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Cited by 16 (2 self)
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We present new bounds on the locality of several classical symmetry breaking tasks in distributed networks. A sampling of the results include 1) A randomized algorithm for computing a maximal matching (MM) in O(log ∆+(log log n) 4) rounds, where ∆ is the maximum degree. This improves a 25year old randomized algorithm of Israeli and Itai that takes O(log n) rounds and is provably optimal for all log ∆ in the range [(log log n) 4, √ log n]. 2) A randomized maximal independent set (MIS) algorithm requiring O(log ∆ √ log n) rounds, for all ∆, and only 2 O(√log log n) rounds when ∆ = poly(log n). These improve on the 25year old O(log n)round randomized MIS algorithms of Luby and Alon, Babai, and Itai when log ∆ ≪ √ log n. 3) A randomized ( ∆ + 1)coloring algorithm requiring O(log ∆ + 2 O(√log log n)) rounds, improving on an algorithm √ of Schneider and Wattenhofer that takes O(log ∆+ log n) rounds. This result implies that an O(∆)coloring can be computed in 2 O(√log log n) rounds for all ∆, improving on Kothapalli et al.’s O ( √ log n)round algorithm. We also introduce a new technique for reducing symmetry breaking problems on low arboricity graphs to low degree graphs. Corollaries of this reduction include MM and MIS algorithms for low arboricity graphs (e.g., planar graphs and graphs that exclude any fixed minor) requiring O ( √ log n) and O(log 2/3 n) rounds w.h.p., respectively.
Toward More Localized Local Algorithms: Removing Assumptions Concerning Global Knowledge
"... Numerous sophisticated local algorithm were suggested in the literature for various fundamental problems. Notable examples are the MIS and ( ∆ + 1)coloring algorithms by Barenboim and Elkin [6], by Kuhn [22], and by Panconesi and Srinivasan [34], as well as the O(∆2)coloring algorithm by Linial [2 ..."
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Cited by 15 (9 self)
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Numerous sophisticated local algorithm were suggested in the literature for various fundamental problems. Notable examples are the MIS and ( ∆ + 1)coloring algorithms by Barenboim and Elkin [6], by Kuhn [22], and by Panconesi and Srinivasan [34], as well as the O(∆2)coloring algorithm by Linial [28]. Unfortunately, most known local algorithms (including, in particular, the aforementioned algorithms) are nonuniform, that is, they assume that all nodes know good estimations of one or more global parameters of the network, e.g., the maximum degree ∆ or the number of nodes n. This paper provides a rather general method for transforming a nonuniform local algorithm into a uniform one. Furthermore, the resulting algorithm enjoys the same asymptotic running time as the original nonuniform algorithm. Our method applies to a wide family of both deterministic and randomized algorithms. Specifically, it applies to almost all of the state of the art nonuniform algorithms regarding MIS and Maximal Matching, as well as to many results concerning the coloring problem. (In particular, it applies to all aforementioned algorithms.) To obtain our transformations we introduce a new distributed tool called pruning algorithms, which we believe may be of independent interest.