mca 16(10): e4

Research Article

Biologically-inspired adaptive routing protocol with stochastic route exploration

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  • @ARTICLE{10.4108/eai.3-12-2015.2262489,
        author={Tomohiro Nakao and Jun-nosuke Teramae and Naoki Wakamiya},
        title={Biologically-inspired adaptive routing protocol with stochastic route exploration},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications},
        keywords={distributed routing, attractor selection, stochastic exploration, a short-term memory},
  • Tomohiro Nakao
    Jun-nosuke Teramae
    Naoki Wakamiya
    Year: 2017
    Biologically-inspired adaptive routing protocol with stochastic route exploration
    DOI: 10.4108/eai.3-12-2015.2262489
Tomohiro Nakao,*, Jun-nosuke Teramae1, Naoki Wakamiya1
  • 1: Osaka University
*Contact email:


Rapid increase in amount of traffic and the number of users of information communication networks requires adaptive routing protocols that can properly respond to unexpected change of communication environment such as rapid and large fluctuation of traffic. While distributed routing protocols that use only local state of the network have been expected to suitable for adaptive routing on large scale net- work, the lack of global information of the network often makes it difficult to promptly respond to traffic changes of the network when it occurs at out of the local scope. In this paper, based on the biologically-inspired attractor selection model, we propose a distributed routing protocol with active and stochastic route exploration. Acquiring current state of the network beyond its local scope by utilizing stochastic nature of the protocol, the routing protocol can efficiently respond to rapid change of traffic demand on the network. In order to avoid destabilization of routings due to the exploration, we introduce a short-term memory term to the governing equation of the protocol. We also confirm that the protocol successfully balances rapid exploration with stable routing owing to the memory term by numerical simulations.