• DocumentCode
    2328273
  • Title

    Towards evolutionary-pricing framework for Mobile Sensor Network self-organization

  • Author

    Marbukh, Vladimir ; Sayrafian-Pour, Kamran ; Mahboubi, Hamid ; Momeni, Ahmadreza ; Aghdam, Amir G.

  • Author_Institution
    Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper reports on work in progress on developing a unified co-evolutionary/pricing framework for Mobile Sensor Networks (MSN) self-organization. MSN self-organization involves cooperative sensor positioning and formation of a multi-hop Mobile Ad-hoc NETwork (MANET) enabling sensor information acquisition and communication while prolonging MSN life-span. A number of inherent MSN traits such as lack of centralized control and variety of performance criteria suggest framing MSN self-organization as a sensor co-evolutionary optimization. The first issue to be addressed is aligning individual sensor utility/fitness landscapes with the overall MSN goals as “selfish” sensor behavior may result in suboptimal overall MSN performance. The paper proposes using “socially optimal pricing” to internalize the effect of each sensor relocation on the overall MSN performance. It is assumed that intermediate nodes in the MSN relay sensor information to a single fusion point without processing. The proposed framework is illustrated for the special case of a MSN tracking a single target.
  • Keywords
    ad hoc networks; evolutionary computation; mobile radio; wireless sensor networks; MANET; MSN life-span; MSN relay sensor; coevolutionary-pricing framework; cooperative sensor formation; cooperative sensor positioning; fitness landscape; mobile sensor network self-organization; multihop mobile ad-hoc network; selfish sensor behavior; sensor coevolutionary optimization; sensor information acquisition; sensor relocation; sensor utility; socially optimal pricing; Batteries; Mobile ad hoc networks; Mobile communication; Mobile computing; Optimization; Robot sensing systems; mobile sensor network; pricing; socially optimal sensor fitness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5586175
  • Filename
    5586175