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Collaboration among mobile agents for efficient energy allocation in mobile grid

Author

Listed:
  • Chunlin Li

    (Wuhan University of Technology)

  • Layuan Li

    (Wuhan University of Technology)

Abstract

The use of mobile devices in grid environments may have two interaction aspects: devices are considered as users of grid resources or as grid resources providers. Due to the limitation constraints on energy and processing capacity of mobile devices, their integration into the Grid is difficult. In this paper, we investigate the cooperation among mobile devices to balance the energy consumption and computation workloads. Mobile devices can have different roles such as buyer devices and seller devices. In the mobile grid, the energies of mobile devices are uneven, energy-poor devices can exploit other devices with spare energy. Our model consists of two actors: A buyer device agent represents the benefits of mobile buyer device that intends to purchase energy from other devices. A seller device agent represents the profits of mobile seller device that is willing to sell spare energy to other devices. The objective of optimal energy allocation in mobile grid is to maximize the utility of the system without exceeding the energy capacity, expense budget and the deadline. A collaboration algorithm among mobile agents for efficient energy allocation is proposed. In the simulation, the performance evaluation of collaboration algorithm among mobile agents is conducted.

Suggested Citation

  • Chunlin Li & Layuan Li, 2012. "Collaboration among mobile agents for efficient energy allocation in mobile grid," Information Systems Frontiers, Springer, vol. 14(3), pages 711-723, July.
    • Handle: RePEc:spr:infosf:v:14:y:2012:i:3:d:10.1007_s10796-011-9298-9
    DOI: 10.1007/s10796-011-9298-9
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    Cited by:

    1. Juan M. Alberola & Luis Búrdalo & Vicente Julián & Andrés Terrasa & Ana García-Fornes, 2014. "An adaptive framework for monitoring agent organizations," Information Systems Frontiers, Springer, vol. 16(2), pages 239-256, April.
    2. Hang Yang & Simon Fong, 2013. "Optimizing dynamic supply chain formation in supply mesh using CSET model," Information Systems Frontiers, Springer, vol. 15(4), pages 569-588, September.
    3. Camarinha-Matos, Luis M., 2016. "Collaborative smart grids – A survey on trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 283-294.
    4. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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