Free-Space Optical Gateway Placement in Hybrid Wireless Mesh Networks

Smadi, M.N.; Ghosh, S.; Farid, A.A.; Todd, T.D.; Hranilovic, Steve

doi:10.1109/jlt.2009.2014910

Cited by 22 publications

(21 citation statements)

References 18 publications

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“…Finally we discuss ways to reduce the computational complexity of the PSC algorithm. There have been a few clustering heuristics in the literature [20,21], and several schemes that consider QoS constraints [9,22]. However, we find it difficult to apply or enhance the existing algorithms for our problem with both traffic demand and delay constraints.…”

Section: Lower Tier: Cluster Formationmentioning

confidence: 99%

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On the design and optimization of a free space optical access network

Son

Mao

Das

2014

Optical Switching and Networking

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Although having high potential for broadband wireless access, wireless mesh networks are known to suffer from throughput and fairness problems, and are thus hard to scale to large size. To this end, hierarchical architectures provide a solution to this scalability problem. In this paper, we address the problem of design and optimization of a tiered wireless access network that exploits free space optical (FSO) communications. The lower tier consists of mesh routers that are clustered based on traffic demands and delay requirements. The cluster heads are equipped with wireless optical transceivers and form the upper tier FSO network. For topology design and optimization, we first present a plane sweeping and clustering (PSC) algorithm aiming to minimize the total number of clusters. PSC sweeps the network area and captures cluster members under delay and traffic load constraints. For the upper tier FSO network, we present an algebraic connectivity-based formulation for topology optimization. We then develop a greedy edge-appending (GEA) algorithm, as well as its distributed version, that iteratively inserts edges to maximize algebraic connectivity. The proposed algorithms are analyzed and evaluated via simulations, and are shown to be highly effective as compared to the performance bounds derived in this paper.

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Section: Lower Tier: Cluster Formationmentioning

confidence: 99%

“…This approach may not be suitable for the case when the mesh routers have different traffic demands. Furthermore, prior work in [9,22] considers only the Internet traffic of the mesh routers, but not the inter-cluster traffic.…”

Section: Lower Tier: Cluster Formationmentioning

confidence: 99%

On the design and optimization of a free space optical access network

Son

Mao

Das

2014

Optical Switching and Networking

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“…There are many researches working on network topology design in traditional wired and optical networks [2], [3], [4], [5]. However, most of them focused on the network construction phase, and did not consider the incremental network upgrade problem.…”

Section: Related Workmentioning

confidence: 99%

Cost-Constrained Incremental Network Planning in Multi-Hop Wireless Networks

Zhang

Cao

Zhang

et al. 2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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In this paper, we investigate the cost-constrained incremental network planning problem in multi-hop wireless networks. Given an existing wireless network, we study the problem of how to add new wireless links to improve the network performance under the deployment cost constraint. After formulating the problem as COst-constrained Incremental Network (COIN) problem, we introduce a performance metric, which represents the tradeoff between throughput improvement and deployment cost. We then propose a Greedy Link Deployment (GLiD) algorithm using the limited-enumeration and greedy searching methods. Finally, through extensive simulations, we evaluate the performance of our algorithm in comparison with other solutions. The results show that our algorithm can perform much better than random deployment and purely greedy deployment methods.Index Terms-Network planning, Multi-hop networks.978-1-4244-9268-8/11/$26.00 ©2011 IEEE This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE Globecom 2011 proceedings.

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“…They emphasized on the cost of FSO transceivers as the major constraint and they showed that the corresponding problem is NP-hard. Smadi et al proposed an algorithm for placing FSO gateways in WMN [6]. Despite the high performance of FSO links in terms of throughput, their reliability is a major issue.…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of FSO Links in Hybrid Wireless Optical Networks

Ahdi

Subramaniam

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Wireless mesh network addresses the last mile issue; however, RF-based technologies are still a bottleneck for todays' media-rich applications. In this paper, we propose enhancing the capacity of an existing wireless mesh backhaul using freespace optical links. Such a hybrid RF/FSO network is capable of multiplying the available bandwidth for each subscriber if the FSO transceivers are placed at strategically located nodes. Adopting a TDMA-based framework, we formulate a problem for the optimal placement of FSO transceivers and RF link activation schedules which maximize the network capacity. An integer-linear program (ILP) is developed to obtain an optimal solution. Due to the complexity of this ILP, we also propose a relaxation which yields an upper bound on the network capacity in such an architecture, and develop a probabilistic heuristic that approaches this capacity. We show by simulations that our heuristic achieves a high fraction of the network capacity upper bound, and it can be implemented efficiently.

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Free-Space Optical Gateway Placement in Hybrid Wireless Mesh Networks

Cited by 22 publications

References 18 publications

On the design and optimization of a free space optical access network

On the design and optimization of a free space optical access network

Cost-Constrained Incremental Network Planning in Multi-Hop Wireless Networks

Optimal Placement of FSO Links in Hybrid Wireless Optical Networks

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