• DocumentCode
    1787415
  • Title

    Proactive Guidance for Dynamic and Cooperative Resource Allocation under Uncertainties

  • Author

    Anders, Gerrit ; Siefert, Florian ; Mair, Michael ; Reif, Wolfgang

  • Author_Institution
    Inst. for Software & Syst. Eng., Augsburg Univ., Augsburg, Germany
  • fYear
    2014
  • fDate
    8-12 Sept. 2014
  • Firstpage
    21
  • Lastpage
    30
  • Abstract
    In many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem in a cooperative manner. If the devices´ ability to change their contribution is subject to inertia, the problem has to be solved proactively. This means that the allocation of resources is scheduled beforehand, based on predictions of the future demand. Because of the scheduling problem´s complexity, schedules should be created rather sporadically for a coarse-grained time pattern. However, because the resource allocation problem has to be solved for all time steps and the demand and provision of resources is uncertain, devices have to reactively adapt their contributions according to the current circumstances. In this paper, we present a mechanism that allows the participants to incorporate the information of proactively created schedules in their reactive decisions in order to steer the system in a stable and efficient way. In particular, the decisions are guided by schedules that already include information about possible uncertainties. While this combination avoids inertia based problems, it significantly reduces the computational costs of searching for high quality solutions. Throughout the paper, the problem of maintaining the balance between energy production and consumption in decentralized autonomous power management systems serves to illustrate our algorithm and results.
  • Keywords
    energy consumption; multi-agent systems; power systems; resource allocation; scheduling; smart power grids; cooperative resource allocation; decentralized autonomous power management systems; dynamic resource allocation; energy consumption; energy production; inertia based problems; proactive guidance; proactively created schedules; scheduling problem complexity; smart grids; Dynamic scheduling; Power generation; Resource management; Robustness; Schedules; Uncertainty; Distributed Problem Solving; Multi-Agent Systems; Resource Allocation Problems; Smart Grids; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptive and Self-Organizing Systems (SASO), 2014 IEEE Eighth International Conference on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/SASO.2014.14
  • Filename
    7000997