ew 18: e16

Research Article

Optimized Geographic Routing in Mobile Ad Hoc Network Using Gray Wolf Optimization

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  • @ARTICLE{10.4108/eai.13-7-2018.162832,
        author={Vimalnath S. and Ravi G.},
        title={Optimized Geographic Routing in Mobile Ad Hoc Network Using Gray Wolf Optimization},
        journal={EAI Endorsed Transactions on Energy Web: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={1},
        keywords={Geographic routing protocol, Gray Wolf Optimization, MANETs, Location Accuracy},
        doi={10.4108/eai.13-7-2018.162832}
    }
    
  • Vimalnath S.
    Ravi G.
    Year: 2020
    Optimized Geographic Routing in Mobile Ad Hoc Network Using Gray Wolf Optimization
    EW
    EAI
    DOI: 10.4108/eai.13-7-2018.162832
Vimalnath S.1,*, Ravi G.2
  • 1: Department of ECE, Paavai Engineering College, Namakkal, India
  • 2: Department of ECE, Sona College of Technology, Salem, India
*Contact email: s.vimal112@gmail.com

Abstract

The geographic routing protocol (GRP) in general seeks the location of sensor nodes to decide the routing path in mobile ad hoc network. This increases the routing overhead while finding the location of nodes. On other hand, the GRP undergoes location inaccuracy and routing void problem. In order to resolve this, in this paper, Gray Wolf Optimization (GWO) is used. This GWO is responsible for proper selection of nodes selected by GRP based on the parameters and selection criteria in order to forward the packets to the next forwarding nodes to reach its destination. The simulation is carried out effectively between the GWO-GRP and existing ACO and fuzzy based GRP with varying network densities. The simulation results show that the GWO-GRP method achieves reduced average delay, increased network lifetime and reduced energy consumption than other methods. Further, it avoids the problems associated with GRP i.e. the location inaccuracy and routing void problem.