• DocumentCode
    2362893
  • Title

    Optimizing network topology to reduce aggregate traffic in a system of mobile robots under an energy constraint

  • Author

    Navaravong, Leenhapat ; Shea, John M. ; Pasiliao, Eduardo L., Jr. ; Dixon, Warren E.

  • Author_Institution
    Univ. of Florida, Gainesville, FL, USA
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    16
  • Lastpage
    20
  • Abstract
    Autonomous mobile robots, such as unmanned aerial or ground vehicles, will play important roles in future military and commercial applications. Future systems will require the robots to communicate with each other on a peer-to-peer basis over a wireless link and are able to form a networked system such as an ad hoc network. In this paper, we consider a problem of optimizing the topology of the network for such systems. Our solution consists of two steps. We first develop a novel method to select a network tree topology from arbitrary initial connected network topology. Second, we develop a new optimization algorithm to reconfigure the network, starting from the tree found in the first step, while maintaining the connectivity to minimize the aggregate traffic under the constraints on the total number of hops that the mobile robots may move. We present simulation results to compare the performance of our algorithms.
  • Keywords
    mobile robots; multi-robot systems; peer-to-peer computing; radio links; telecommunication network topology; trees (mathematics); aggregate traffic reduction; arbitrary initial connected network topology; autonomous mobile robots; commercial applications; energy constraint; military applications; network tree topology optimization; networked system; peer-to-peer basis; wireless link; Aggregates; Complexity theory; Mobile robots; Network topology; Simulated annealing; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2012 IEEE International Conference on
  • Conference_Location
    Ottawa, ON
  • ISSN
    1550-3607
  • Print_ISBN
    978-1-4577-2052-9
  • Electronic_ISBN
    1550-3607
  • Type

    conf

  • DOI
    10.1109/ICC.2012.6363692
  • Filename
    6363692