An Integrated Data Combination Method in Wireless Sensor Networks

Yang Zhang, Yun Liu, Qing-An Zeng and Qing Liu
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Yang Zhang: School of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing, China
Yun Liu: School of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing, China
Qing-An Zeng: Department of Computer Systems Technology, North Carolina A&T State University, Greensboro, USA
Qing Liu: China Electric Power Construction Limited by Share Ltd, Beijing, China

International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 2018, vol. 10, issue 4, 61-76

Abstract: This article proposes an integrated information fusion approach in wireless sensor networks (WSNs) based on the Dempster-Shafer evidence theory, which includes four main aspects: the construction of basic probability assignment; a novel reliability coefficient function converting similarity to initial weight factors; an improved fusion approach by reassigning reliability coefficients; and the “Discount Rule.” Utilizing the integrated approach, conflicting data are fused more accurately and effectively than using the traditional fusion method. Experimental results show that the combined belief assignment of the proposed approach is in accordance with the real data observations. The integrated information combination rule for combining conflicting data can avoid the influence of imprecise information from sensors, and has the better performance than other conventional methods.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jitn00:v:10:y:2018:i:4:p:61-76

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