A Novel Link Quality Prediction Algorithm forWireless Sensor Networks

Chenhao Jia1, Linlan Liu1, Xiaole Gu1 and Manlan Liu1

  1. Internet of Things Technology Institute, Nanchang Hangkong University
    330063 Nanchang, China
    1127792870@qq.com, liulinlan@nchu.edu.cn, 1030697096@qq.com, 694531775@qq.com


Ahead knowledge of link quality can reduce the energy consumption of wireless sensor networks. In this paper, we propose a cloud reasoning-based link quality prediction algorithm for wireless sensor networks. A large number of link quality samples are collected from different scenarios, and their RSSI, LQI, SNR and PRR parameters are classified by a self-adaptive Gaussian cloud transformation algorithm. Taking the limitation of nodes’ resources into consideration, the Apriori algorithm is applied to determine association rules between physical layer and link layer parameters. A cloud reasoning algorithm that considers both short- and long-term time dimensions and current and historical cloud models is then proposed to predict link quality. Compared with the existing window mean exponentially weighted method, the proposed algorithm captures link changes more accurately, facilitating more stable prediction of link quality.

Key words

wireless sensor networks, link quality prediction, Gaussian cloud transformation

Digital Object Identifier (DOI)


Publication information

Volume 14, Issue 3 (September 2017)
Advances in Information Technology, Distributed and Model Driven Systems
Year of Publication: 2017
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Jia, C., Liu, L., Gu, X., Liu, M.: A Novel Link Quality Prediction Algorithm forWireless Sensor Networks. Computer Science and Information Systems, Vol. 14, No. 3, 719–734. (2017), https://doi.org/10.2298/CSIS161220025J