A Multivariate-Time-Series-Prediction-Based Adaptive Data Transmission Period Control Algorithm for IoT Networks
- Authors
- Han, Jaeseob; Lee, Gyeong Ho; Park, Sangdon; Lee, Joohyung; Choi, Jun Kyun
- Issue Date
- Jan-2022
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Convolutional neural network (CNN); data transmission period; Internet of Things (IoT)
- Citation
- IEEE INTERNET OF THINGS JOURNAL, v.9, no.1, pp.419 - 436
- Journal Title
- IEEE INTERNET OF THINGS JOURNAL
- Volume
- 9
- Number
- 1
- Start Page
- 419
- End Page
- 436
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/83181
- DOI
- 10.1109/JIOT.2021.3124673
- ISSN
- 2327-4662
- Abstract
- In order to reduce unnecessary data transmissions from Internet of Things (IoT) sensors, this article proposes a multivariate-time-series-prediction-based adaptive data transmission period control (PBATPC) algorithm for IoT networks. Based on the spatio-temporal correlation between multivariate time-series data, we developed a novel multivariate time-series data encoding scheme utilizing the proposed time-series distance measure ADMWD. Composed of two significant factors for a multivariate time-series prediction, i.e., the absolute deviation from the mean (ADM) and the weighted differential (WD) distance, the ADMWD considers both the time distance from a prediction point and a negative correlation between the time-series data concurrently. Utilizing the convolutional neural network (CNN) model, a subset of IoT sensor readings can be predicted from encoded multivariate time-series measurements, and we compared the predicted sensor values with actual readings to obtain the adaptive data transmission period. Extensive performance evaluations show a substantial performance gain of the proposed algorithm in terms of the average power reduction ratio (approximately 12%) and average data reconstruction error (approximately 8.32% MAPE). Finally, this article also provides a practical implementation of the proposed PBATPC algorithm via the HTTP protocol under the IEEE 802.11-based WLAN network.
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