Low-Complexity Distributed Scheduling Algorithms for Wireless Networks

Gupta, Abhinav; Lin, Xiaojun; Srikant, R.

doi:10.1109/infcom.2007.191

Cited by 124 publications

(94 citation statements)

References 22 publications

(24 reference statements)

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“…‡ The authors in Reference [8] further show that g(M) = ( √ M − 1)/2 results in a (1/2 − 1/ √ M)-throughput optimal scheduler. Using Type II algorithms, the authors of Reference [10] show that with g(M) = log(2M)/2, the achieved throughput ratio is at least 1 2 − log(2M) 2M , which outperforms Type I algorithms.…”

Section: Random Access Schemes With Constant Time Control Phasementioning

confidence: 99%

Towards utility‐optimal random access without message passing

Liu

Proutière

et al. 2009

Wireless Communications

107

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It has been recently suggested by Jiang and Walrand that adaptive carrier sense multiple access (CSMA) can achieve optimal utility without any message passing in wireless networks. In this paper, after a survey of recent work on random access, a generalization of this algorithm is considered. In the continuous-time model, a proof is presented of the convergence of these adaptive CSMA algorithms to be arbitrarily close to utility optimality, without assuming that the network dynamics converge to an equilibrium in between consecutive CSMA parameter updates. In the more realistic, slotted-time model, the impact of collisions on the utility achieved is characterized, and the tradeoff between optimality and short-term fairness is quantified.

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Section: Random Access Schemes With Constant Time Control Phasementioning

confidence: 99%

Towards utility‐optimal random access without message passing

Liu

Proutière

et al. 2009

Wireless Communications

107

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“…Collect Q(t) and S ij (t − 1). 8: 12: S ij (t) = X ij (t); 13: end if 14: Broadcast RESULT(S ij (t)) in super-subSquare(i, j); 15: end if 16: if state = White then 17: if receive message RESULT(S ij (t)) then 18: if v ∈ S ij (t) then 19: state = Red; active = Yes; 20: else 21: state = Black; active = No; 22: end if 23: end if 24: end if…”

Section: B Detailed Descriptionmentioning

confidence: 99%

Throughput Optimizing Localized Link Scheduling for Multihop Wireless Networks under Physical Interference Model

Zhou

Liu

et al. 2014

IEEE Trans. Parallel Distrib. Syst.

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We study throughput-optimum localized link scheduling in wireless networks. The majority of results on link scheduling assume binary interference models that simplify interference constraints in actual wireless communication. While the physical interference model reflects the physical reality more precisely, the problem becomes notoriously harder under the physical interference model. There have been just a few existing results on link scheduling under the physical interference model, and even fewer on more practical distributed or localized scheduling. In this paper, we tackle the challenges of localized link scheduling posed by the complex physical interference constraints. By integrating the partition and shifting strategies into the pick-and-compare scheme, we present a class of localized scheduling algorithms with provable throughput guarantee subject to physical interference constraints. The algorithm in the oblivious power setting is the first localized algorithm that achieves at least a constant fraction of the optimal capacity region subject to physical interference constraints. The algorithm in the uniform power setting is the first localized algorithm with a logarithmic approximation ratio to the optimal solution. Our extensive simulation results demonstrate performance efficiency of our algorithms.Index Terms-Localized link scheduling, physical interference model, maximum weighted independent set of links (MWISL), capacity region

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“…In order to sell its channel a primary needs to find a set of locations which do not interfere with each other. Wireless networks have been traditionally modeled as conflict graphs (Figures 1, 2, 3) in most of the existing literature including in several seminal papers [28]- [30]. Let G = (V, E) be the overall conflict graph of the region where V is the set of nodes and E is the set of edges; an edge exists between two nodes iff transmission at the corresponding locations interfere.…”

Section: Conflict Graphmentioning

confidence: 99%

Quality sensitive price competition in spectrum oligopoly over multiple locations

Ghosh

Sarkar

2014

2014 48th Annual Conference on Information Sciences and Systems (CISS)

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We investigate a spectrum oligopoly market where each primary seeks to sell secondary access to channels at multiple locations. Transmission qualities of a channel evolve randomly. Each primary needs to select a price and a set of noninterfering locations (which is the independent set in the conflict graph of the region) at which to offer its channel without knowing the transmission qualities of the channels of its competitors. Secondaries select a channel depending on the price and the quality the channel offers. We formulate the above problem as a non-cooperative game theoretic problem. We focus on a class of conflict graphs, known as mean valid graphs which commonly arise in practice. We explicitly compute a symmetric Nash equilibrium (NE) that selects only a small number of independent sets with positive probability. The NE is threshold type in that primaries do not choose independent sets whose cardinality fall below a certain threshold. The threshold on the cardinality increases with increase in quality of the channel on sale.

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Low-Complexity Distributed Scheduling Algorithms for Wireless Networks

Cited by 124 publications

References 22 publications

Towards utility‐optimal random access without message passing

Towards utility‐optimal random access without message passing

Throughput Optimizing Localized Link Scheduling for Multihop Wireless Networks under Physical Interference Model

Quality sensitive price competition in spectrum oligopoly over multiple locations

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