In this paper, we propose QNGPSR, a Q-network enhanced geographic routing protocol based on well-known GPSR for the ad-hoc network. By using the reinforcement learning and neighbor topology information to make next-hop selection in multiple available paths, the probability of exploiting perimeter forwarding mode that may induce network delay can be greatly reduced. We evaluate the performance of QNGPSR in comparison with OLSR, AODV and GPSR. The simulation results show that the proposed protocol obtains a higher packet delivery ratio and a lower end-to-end delay compared with the original GPSR. In high node density and high mobility scenarios, the performance of QNGPSR is better than OLSR and AODV.


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    Titel :

    QNGPSR: A Q-Network Enhanced Geographic Ad-Hoc Routing Protocol Based on GPSR


    Beteiligte:
    Lyu, Niqi (Autor:in) / Song, Guanghua (Autor:in) / Yang, Bowei (Autor:in) / Cheng, Yining (Autor:in)


    Erscheinungsdatum :

    01.08.2018


    Format / Umfang :

    691476 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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