ChinaCom2009-Wireless Communications and Networking Symposium

Research Article

Optimization of Energy Consumption in Rectangular Ad-hoc Wireless networks

  • @INPROCEEDINGS{10.1109/CHINACOM.2009.5339843,
        author={Wei Feng and Hamada Alshaer and Jaafar M.Electronic and Electrical Engineering, University of Leeds, Leeds, UK, LS2 9JT. and H. Elmirghani},
        title={Optimization of Energy Consumption in Rectangular Ad-hoc Wireless networks},
        proceedings={ChinaCom2009-Wireless Communications and Networking Symposium},
        publisher={IEEE},
        proceedings_a={CHINACOM2009-WCN},
        year={2009},
        month={11},
        keywords={Energy efficiency ad-hoc network optimal radio range topology management. I. INTRODUCTION},
        doi={10.1109/CHINACOM.2009.5339843}
    }
    
  • Wei Feng
    Hamada Alshaer
    Jaafar M.Electronic and Electrical Engineering, University of Leeds, Leeds, UK, LS2 9JT.
    H. Elmirghani
    Year: 2009
    Optimization of Energy Consumption in Rectangular Ad-hoc Wireless networks
    CHINACOM2009-WCN
    IEEE
    DOI: 10.1109/CHINACOM.2009.5339843
Wei Feng1, Hamada Alshaer1, Jaafar M.Electronic and Electrical Engineering, University of Leeds, Leeds, UK, LS2 9JT., H. Elmirghani1
  • 1: Electronic and Electrical Engineering, University of Leeds, Leeds, UK, LS2 9JT.

Abstract

Wireless ad hoc networks operation is constrained by energy consumption of every network nodes. To this end, this paper, based on Geographical Adaptive Fidelity (GAF) topology management protocol [1], analyzes the energy consumption in a rectangular ad-hoc wireless network. Three GAF models for energy efficiency are introduced and discussed: equal-grid, adjustable-grid and genetic algorithm models. In the equal and adjustable-grid models, the optimal transmission range corresponding to the minimum energy consumption has been derived, meanwhile the third model is based on on a genetic algorithm introduced to save energy consumption in rectangular ad hoc networks. Results based on numerical analysis show that the genetic-algorithm model outperforms the equal and adjustablegrid models in term of energy consumption. Finally, we simulate a network model in which nodes can transmit at different transmission ranges, where the GAF models including the genetic algorithm model show better saving in energy consumption than those GAF models based on static transmission range.