A Novel Link Quality Prediction Algorithm forWireless Sensor Networks

Computer Science and Information Systems

Chenhao Jia¹ 

[1] Internet of Things Technology Institute, Nanchang Hangkong University

关键词: wireless sensor networks;    link quality prediction;    Gaussian cloud transformation;   

DOI  :  10.2298/CSIS161220025J

学科分类：社会科学、人文和艺术（综合）

来源: Computer Science and Information Systems

【 摘 要 】

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.

【 授权许可】

CC BY-NC-ND