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Research on Repair Method of Data Forwarding Link in Internet of Things Based on Fuzzy Decision

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Published:21 December 2018Publication History

ABSTRACT

In the future, the number of nodes in the Internet of Things wireless network is huge and diverse. The difference in energy consumption, transmission distance, and mobility of nodes causes the instability of communication links between nodes. The original data link is established along with the network. Changes in the environment are more likely to fail. The link repair process needs to be initiated after the data transmission link fails. However, in most cases, there are multiple repair links. The selection of the repair link often affects the later link repair process. In order to reduce the subsequent route repair overhead and reduce the network communication delay, the link with better life cycle and better stability in the IoT is selected for repair. A link repair method based on the Internet of Things for wireless transmission system is proposed. Firstly, the method uses the residual energy of the node, the signal strength of the node, the position and movement of the node, the number of hops of the node and other factors that affect the stability of the routing link as the input of the fuzzy control. Secondly, the fuzzy control rule is established and the fuzzy control rule is used to infer the The decision parameters of the nodes on the link, and finally map the decision parameters to the damaged link to determine the optimal link for repair. The experimental results show that the repair method can select the optimal link in the damaged link and reduce the subsequent route repair overhead and network communication delay by repairing the optimal link.

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    • Published in

      cover image ACM Other conferences
      ACAI '18: Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence
      December 2018
      460 pages
      ISBN:9781450366250
      DOI:10.1145/3302425

      Copyright © 2018 ACM

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      Publication History

      • Published: 21 December 2018

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      ACAI '18 Paper Acceptance Rate76of192submissions,40%Overall Acceptance Rate173of395submissions,44%
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