Dormancy strategy for temporal-spatial correlated nodes in wireless sensor networks

Jiang Yu; Yu Meng; Xingchuan Liu; Yongjie Nie

doi:10.1117/12.2667233

22 February 2023 Dormancy strategy for temporal-spatial correlated nodes in wireless sensor networks

Jiang Yu, Yu Meng, Xingchuan Liu, Yongjie Nie

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 125871E (2023) https://doi.org/10.1117/12.2667233
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

Reducing network power consumption plays an important role in the research of wireless sensor networks. This paper focuses on energy efficiency in environmental data collection scenarios. The data collected in this scenario are usually redundant due to spatial and temporal correlation. Consequently, selecting some nodes for dormancy can reduce power consumption. It is the key issue that how to select dormant nodes, and existing research mainly focuses on uniform clustering and optimal routing algorithms. However, the algorithms cannot guide the selection of dormant nodes because of their less consideration of attribute characteristics. Therefore, this paper proposes a node dormancy strategy for temporal-spatial correlated nodes in wireless sensor networks. The temporal-spatial correlation of the data is firstly verified; then the attributes combined with the location information are provided for FCM clustering; after, dormant node selection and head node selection are performed according to the clustering. Experiments on real temperature datasets demonstrate that using this paper's strategy, data accuracy can still be maintained at more than 95% of what no dormant node perform when 50% of nodes are dormant and around 90% when 80% of nodes are dormant. The improvement even reaches at most 80% against the traditional strategy with the same percentage of dormancy.

Citation Download Citation

Jiang Yu, Yu Meng, Xingchuan Liu, and Yongjie Nie "Dormancy strategy for temporal-spatial correlated nodes in wireless sensor networks", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 125871E (22 February 2023); https://doi.org/10.1117/12.2667233

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KEYWORDS

Sensor networks

Data conversion

Temperature metrology

Algorithm development

Fuzzy logic

Raster graphics

Data processing

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