Decentralized TDMA for IoT networks based on synchronization theory with intermittent communication

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Abstract
For the Internet of Things (IoT) comprising large-scale networks composed of tiny devices with limited resources, decentralized management is necessary to avoid an increase in load and cost from control signals; in addition, power-saving protocols such as intermittent communications are also essential. Carrier sense multiple access with collision avoidance (CSMA/CA) and time division multiple access (TDMA) have been used as one medium access control protocols in such environments, and CSMA/CA is one of the random access protocols which can be applied to the decentralized system; however, it causes significant delays by stochastic collisions in congested environments. Desynchronization is one of the concepts for decentralized TDMA, and the possibility of a collision can be reduced based on evenly distributed phases by interaction based on the phase differences. There are several desynchronization models, such as the Kuramoto-based model; however, these Kuramoto-based models have not been designed and implemented for IoT devices; it needs to exchange phase information continuously with others within sending cycles, thus, making it difficult to achieve ON/OFF scheduling in one cycle, intermittent communication. To make it applicable to IoT devices, we propose an intermittent inhibitory-coupled Kuramoto oscillator model in this paper. IoT devices can achieve autonomous scheduling to avoid collisions even in high-density environments by the proposed method; therefore, it can guarantee communication quality, moreover, be applied to power-saving IoT devices that use intermittent communication. Simulations and experiments have shown the effectiveness of the proposed method in the environments in both static networks and dynamical networks, supposing mobile environments. Furthermore, compared to CSMA/CA, the proposed method obtains a higher packet success rate than CSMA/CA.
Funding Information
  • Japan Society for the Promotion of Science (JP23K13331)
  • Moonshot Research and Development Program (JPMJMS2021)
  • International Research Center for Neurointelligence, University of Tokyo
  • Institute of AI and Beyond of UTokyo
  • Council for Science, Technology and Innovation (JPJ012207)

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