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Link-delay-aware Reinforcement Scheduling for Data Aggregation in Massive IoT
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  • Van-Vi Vo ,
  • Tien-Dung Nguyen ,
  • Duc-Tai Le ,
  • Moonseong Kim ,
  • Hyunseung Choo
Van-Vi Vo
Sungkyunkwan University

Corresponding Author:[email protected]

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Tien-Dung Nguyen
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Duc-Tai Le
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Moonseong Kim
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Hyunseung Choo
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Over the past few years, the use of wireless sensor networks in a range of Internet of Things (IoT) scenarios has grown in popularity. Since IoT sensor devices have restricted battery power, a proper IoT data aggregation approach is crucial to prolong the network lifetime. To this end, current approaches typically form a virtual aggregation backbone based on a connected dominating set or maximal independent set to utilize independent transmissions of dominators. However, they usually have a fairly long aggregation delay because the dominators become bottlenecks for receiving data from all dominatees. The problem of time-efficient data aggregation in multichannel duty-cycled IoT sensor networks is analyzed in this paper. We propose a novel aggregation approach, named LInk-delay-aware REinforcement (LIRE), leveraging active slots of sensors to explore a routing structure with pipeline links, then scheduling all transmissions in a bottom-up manner. The reinforcement schedule accelerates the aggregation by exploiting unused channels and time slots left off at every scheduling round. LIRE is evaluated in a variety of simulation scenarios through theoretical analysis and performance comparisons with a state-of-the-art scheme. The simulation results show that LIRE reduces more than 80% aggregation delay compared to the existing scheme.
Aug 2022Published in IEEE Transactions on Communications volume 70 issue 8 on pages 5353-5367. 10.1109/TCOMM.2022.3186407