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Cross-Layer Capacity Estimation and Throughput Maximization in Wireless Networks

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Abstract

In this chapter, we explore techniques for capacity estimation and throughput maximization in multi-hop wireless networks. The specific problem we investigate is the following: how can we characterize the set of all feasible end-to-end connection throughput rate vectors which can be supported by the network (i.e., what is the network capacity), and how can we design cross-layer algorithms at the scheduling, routing, and transport layers which are guaranteed to operate the network close to its capacity? We approach this problem from three distinct perspectives which have greatly influenced research in this field: (1) throughput scaling in random geometric graphs whose nodes are distributed uniformly in space, (2) geometric packing and linear programming-based techniques for arbitrary networks, and (3) the dynamic back-pressure scheme based on queueing theoretic principles for achieving network stability. A recurring theme throughout this chapter is the role of geometric insights into the design and analysis of provably good algorithms for multi-hop wireless networks. We also include a brief survey of related developments in the field of cross-layer algorithms for multi-hop wireless networks.

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Notes

  1. 1.

    Note that the size of the square does not vary with n. The results discussed here will change if the size of the square varies with n.

  2. 2.

    { E}[ ⋅] denotes expectation over a distribution which is usually clear from the context.

  3. 3.

    Recall that an α-approximation algorithm for a maximization problem is one which is always guaranteed to produce a solution whose value is within a factor of α from that of the optimal solution.

  4. 4.

    The network layer capacity region consists of all connection rate vectors that can be stably scheduled by any routing and scheduling strategy. This notion is made rigorous in Section 5.5.1.

  5. 5.

    For ease of exposition, we will not consider the time varying aspects of the algorithm in this chapter.

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Acknowledgements

V.S. Anil Kumar and Madhav Marathe are partially supported by the following grants from NSF: CNS-0626964, SES-0729441, CNS-0831633, and CNS CAREER 0845700.

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Authors and Affiliations

  1. Department of Computer Science and Virginia BioInformatics Institute, Virginia Tech, Blacksburg, VA, 24061, U.S.A.

    V. S. Anil Kumar & Madhav V. Marathe

  2. T. J. Watson Research Center, IBM, Hawthorne, NY, 10532, U.S.A.

    Srinivasan Parthasarathy

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Correspondence to V. S. Anil Kumar .

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    Graham Cormode

  2. Networking Research Lab., Bell Labs, Mountain Ave. 600-700, Murray Hill, 07974, U.S.A.

    Marina Thottan

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Kumar, V.S.A., Marathe, M.V., Parthasarathy, S. (2010). Cross-Layer Capacity Estimation and Throughput Maximization in Wireless Networks. In: Cormode, G., Thottan, M. (eds) Algorithms for Next Generation Networks. Computer Communications and Networks. Springer, London. https://doi.org/10.1007/978-1-84882-765-3_5

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