4.7 Article

An Effective Early Message Ahead Join Adaptive Data Aggregation Scheme for Sustainable IoT

Journal

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TNSE.2020.3033938

Keywords

Data aggregation; Sensors; Wireless sensor networks; Routing; Delays; Energy consumption; Monitoring; Data Aggregation; Delay; IoT; Network lifetime; Wireless sensor networks

Funding

  1. National Natural Science Foundation of China [62072475, 61772554]

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The paper proposes two data aggregation schemes for IoT, one based on an advance notification mechanism and the other combining advance notification mechanism and convergence routings. These schemes aim to optimize energy consumption, improve network lifetime, and reduce transmission latency in data collection.
The rapid development of Internet of Things (IoT) can promote the establishment of the smart connected world by using numerous devices and sensors. Collecting the data perceived by sensing devices in a fast and energy-saving style is critical for building a stable network in IoT. In this paper, we propose an Early Message Ahead Join Adaptive Data Aggregation (E-ADA) scheme for IoT. Firstly, an advance notification mechanism based on early message is introduced to improve the probability of data aggregation, thus optimizing energy consumption and network lifetime. In this mechanism, the routing of early message is faster than that of the data packet. Nodes with data packet send an early message forward to notice, and other data packets which monitor the early message can wait for that to aggregate under the delay deadline constraints. Secondly, we propose a Delay-optimized Convergence Routing based E-ADA (DOCR-E-ADA) data collection scheme which combines advance notification mechanism and convergence routings. The duty cycle of nodes in convergence routing is adaptively adjusted, which greatly reduces transmission latency. Finally, extensive experimental results demonstrate that our DOCR-E-ADA outperforms the existing schemes in terms of network delay and lifetime.

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