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Prediction-based data reduction with dynamic target node selection in IoT sensor networks
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DOI：10.1016/j.future.2023.11.007.png)
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摘要
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In various applications of IoT sensor networks, special attention is paid to sensor nodes that register higher or lower values of a monitored parameter compared to other nodes. Thus, methods are necessary that enable the selection of target nodes while minimizing the number of data transmissions. The reduced amount of data transmitted during target node selection contributes to energy savings and prolongs the lifetime of battery-powered sensor nodes. This paper introduces a method for reducing data transmissions in sensor networks, where target nodes are selected to perform monitoring tasks. The proposed method allows the IoT gateway to determine when the sensor nodes should report their data readings. The gateway utilizes a prediction algorithm to determine whether a new target node should be selected. In this scheme, data are transmitted only when necessary for the correct selection of the target node. Experiments were conducted for a wireless sensor network consisting of mobile devices, where the target node is the device closest to a given location. The experimental evaluation confirmed that the proposed method significantly reduces the amount of transmitted data and ensures the proper selection of the target node. It was also demonstrated that the introduced approach reduces data transmissions more effectively than the state-of-the-art prediction-based algorithms. During the experiments, the amount of data transmitted from sensor nodes to the IoT gateway was analyzed. The proposed method has reduced the amount of transmissions by 94%, while the highest transmission reduction rate achieved by the existing techniques was 81.4%.
Keyword:
Internet of Things
Wireless sensor networks
Transmission reduction
Prediction
Proximity monitoring
Mobile computing
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