Mesh networks: commodity multihop ad hoc networks

Bruno, Raffaele; Conti, Marco; Gregori, Enrico

doi:10.1109/mcom.2005.1404606

Cited by 714 publications

(334 citation statements)

References 10 publications

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“…There is a considerable literature on WMN networking technology and its applications, see, for example, surveys in [7,8,19], and introductory discussions in [26,32]. Also, optimization techniques have been extensively studied in the literature to, generally speaking, maximize the network capacity.…”

Section: Survey Of the Fieldmentioning

confidence: 99%

“…Although formulation (21) looks more complicated than (18), it turns out that compatible sets are generated in the same way as before, i.e., by solving (19). The reason is that in an optimal dual solution all variables β m vi can be made equal to 0.…”

Section: Non-compact Formulation and Compatible Sets Generationmentioning

confidence: 99%

“…The idea of WMN stems from the ad-hoc networking paradigm and, as such, fits very well the decentralized philosophy of the Internet. For comprehensive surveys of WMN, we refer to [7,19].…”

Section: Introductionmentioning

confidence: 99%

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On max–min fair flow optimization in wireless mesh networks

et al. 2014

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The paper is devoted to modeling wireless mesh networks (WMN) through mixed-integer programming (MIP) formulations that allow to precisely characterize the link data rate capacity and transmission scheduling using the notion of time slots. Such MIP models are formulated for several cases of the modulation and coding schemes (MCS) assignment. We present a general way of solving the max-min fairness (MMF) traffic objective for WMN using the formulated capacity models. Thus the paper combines WMN radio link modeling with a non-standard way of dealing with uncertain traffic, a combination that has not, to our knowledge, been treated so far by exact optimization models. We discuss several ways, including a method based on the so called compatible or independent sets, of solving the arising MIP problems. We also present an extensive numerical study that illustrates the running time efficiency of different solution approaches, and the influence of the MCS selection options and the number of time slots on traffic performance of a WMN. Exact joint optimization modeling of the WMN capacity and the MMF traffic objectives forms the main contribution of the paper.

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Section: Survey Of the Fieldmentioning

confidence: 99%

Section: Non-compact Formulation and Compatible Sets Generationmentioning

confidence: 99%

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On max–min fair flow optimization in wireless mesh networks

et al. 2014

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“…Given an arbitrary channel assignment vector x Àn , we also define: X n ðx Àn Þ ¼ fx : x 2 X; x Àn ¼x Àn g: ð24Þ 2 The Hadamard product of two C Â C matrices A and B is a C Â C matrix whose entry in the uth row and vth column is equal to the product of the entry in the uth row and vth column of A and the entry in the uth row and vth column of B [43].…”

Section: Distributed Congestion-aware Channel Assignment (Dcaca) Algomentioning

confidence: 99%

“…Some of the routers also act as gateways to the Internet via high-speed wired links. Mobile devices first transfer data to their associated router, and the data is then transferred to the Internet via the intermediate routers in a multi-hop manner [1,2].…”

Section: Introductionmentioning

confidence: 99%

Congestion-aware channel assignment for multi-channel wireless mesh networks

Rad

Wong

2009

Computer Networks

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a b s t r a c tIn this paper, we propose a distributed congestion-aware channel assignment (DCACA) algorithm for multi-channel wireless mesh networks (MC-WMNs). The frequency channels are assigned according to the congestion measures which indicate the congestion status at each link. Depending on the selected congestion measure (e.g., queueing delay, packet loss probability, and differential backlog), various design objectives can be achieved. Our proposed distributed algorithm is simple to implement as it only requires each node to perform a local search. Unlike most of the previous channel assignment schemes, our proposed algorithm assigns not only the non-overlapped (i.e., orthogonal) frequency channels, but also the partially-overlapped channels. In this regard, we introduce the channel overlapping and mutual interference matrices which model the frequency overlapping among different channels. Simulation results show that in the presence of elastic traffic (e.g., TCP Vegas or TCP Reno) sources, our proposed DCACA algorithm increases the aggregate throughput and also decreases the average packet round-trip compared with the previously proposed Load-Aware channel assignment algorithm. Furthermore, in a congested IEEE 802.11b network setting, compared with the use of three non-overlapped channels, the aggregate network throughput can further be increased by 25% and the average round-trip time can be reduced by more than one half when all the 11 partially-overlapped channels are used.

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Encoding for Efficient Data Distribution in Multihop Ad Hoc Networks

Boukerche

2008

Algorithms and Protocols for Wireless and Mobile Ad Hoc Networks

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Mesh networks: commodity multihop ad hoc networks

Cited by 714 publications

References 10 publications

On max–min fair flow optimization in wireless mesh networks

On max–min fair flow optimization in wireless mesh networks

Congestion-aware channel assignment for multi-channel wireless mesh networks

Encoding for Efficient Data Distribution in Multihop Ad Hoc Networks

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