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NEWTR: a multipath routing for next hop destination in internet of things with artificial recurrent neural network (RNN)

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Abstract

Internet of Things (IoT) and Wireless Sensor Networks (WSN) are a set of low-cost wireless sensors that can collect, process and send environment’s data. WSN nodes are battery powered, therefore energy management is a key factor for long live network. One way to prolong lifetime of network is to utilize routing protocols to manage energy consumption. To have an energy efficient protocol in environment interactions, we can apply ZigBee protocols. Among these Artificial Intelligence Interactions routing methods, Tree Routing (TR) that acts in the tree network topology is considered a simple routing protocol with low overhead for ZigBee. In a tree topology, every nodes can be recognized as a parent or child of another node and in this regard, there is no circling. The most important problem of TR is increasing the number of steps to get data to the destination. To solve this problem several algorithms were proposed that its focus is on fewer steps. In this research we present an artificial Intelligence Tree Routing based on RNN and ZigBee protocol in IoT environment. Simulation results show that NEWTR improve the network lifetime by 5.549% and decreases the energy consumption (EC) of the network by 5.817% as compared with AODV routing protocol.

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Authors and Affiliations

  1. Department of CSE, KPR Institute of Engineering and Technology, Coimbatore, India

    A. C. Sumathi

  2. Department of Computer Science and Technology, Cyberspace Security, Harbin Institute of Technology, Shenzhen, 518055, China

    Amir Javadpour

  3. Electrotechnics and Telecommunications Department, ADiT-Lab, Instituto Politécnico de Viana do Castelo (IPVC), Porto, Portugal

    Amir Javadpour & Pedro Pinto

  4. School of Computing Science and Engineering, VIT University, Vellore, India

    Arun Kumar Sangaiah

  5. National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliu, Taiwan

    Arun Kumar Sangaiah

  6. Department of Computer Science and Technology, Peng Cheng Laboratory & Harbin Institute of Technology, Shenzhen, 518055, China

    Weizhe Zhang

  7. Department of Computer Science and Engineering, USM Engineering Campus, 14300, Nibong Tebal, Pulau Pinang, Malaysia

    Shadi Mahmoodi Khaniabadi

Authors
  1. A. C. Sumathi
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  2. Amir Javadpour
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  3. Pedro Pinto
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  4. Arun Kumar Sangaiah
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  5. Weizhe Zhang
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  6. Shadi Mahmoodi Khaniabadi
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Corresponding authors

Correspondence to Amir Javadpour, Arun Kumar Sangaiah or Weizhe Zhang.

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Sumathi, A.C., Javadpour, A., Pinto, P. et al. NEWTR: a multipath routing for next hop destination in internet of things with artificial recurrent neural network (RNN). Int. J. Mach. Learn. & Cyber. 13, 2869–2889 (2022). https://doi.org/10.1007/s13042-022-01568-w

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  • DOI: https://doi.org/10.1007/s13042-022-01568-w

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