IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-1-4614-0857-4_8.html
   My bibliography  Save this book chapter

On Throughput Maximization Problem for UWB-Based Sensor Networks via Reformulation–Linearization Technique

In: Handbook of Optimization in Complex Networks

Author

Listed:
  • Yi Shi

    (Virginia Polytechnic Institute and State University)

  • Y. Thomas Hou

    (Virginia Polytechnic Institute and State University)

  • Hanif D. Sherali

    (Virginia Polytechnic Institute and State University)

Abstract

Nonlinear optimization problems (if not convex) are NP-hard in general. One effective approach to develop efficient solutions for these problems is to apply the branch-and-bound (BB) framework. A key step in BB is to obtain a tight linear relaxation for each nonlinear term. In this chapter, we show how to apply a powerful technique, called Reformulation–Linearization Technique (RLT), for this purpose. We consider a throughput maximization problem for an ultra-wideband (UWB)-based sensor network. Given a set of source sensor nodes in the network with each node generating a certain data rate, we want to determine whether or not it is possible to relay all these rates successfully to the base station. We formulate an optimization problem, with joint consideration of physical layer power control, link layer scheduling, and network layer routing. We show how to solve this nonlinear optimization problem by applying RLT and BB. We also use numerical results to demonstrate the efficacy of the proposed solution.

Suggested Citation

  • Yi Shi & Y. Thomas Hou & Hanif D. Sherali, 2012. "On Throughput Maximization Problem for UWB-Based Sensor Networks via Reformulation–Linearization Technique," Springer Optimization and Its Applications, in: My T. Thai & Panos M. Pardalos (ed.), Handbook of Optimization in Complex Networks, chapter 0, pages 219-239, Springer.
    • Handle: RePEc:spr:spochp:978-1-4614-0857-4_8
    DOI: 10.1007/978-1-4614-0857-4_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:spochp:978-1-4614-0857-4_8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.