3D Terrain Multiobjective Deployment Optimization of Heterogeneous Directional Sensor Networks in Security Monitoring

The traditional deployment research on wireless sensor networks (WSNs) has mainly focused on 2D plane and 3D full space; also, the sensors considered are almost always omni-directional sensors and are usually homogeneous. However, this type of research cannot fulfill the diverse requirements require...

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Vydáno v:IEEE transactions on big data Ročník 5; číslo 4; s. 495 - 505
Hlavní autoři: Cao, Bin, Zhao, Jianwei, Lv, Zhihan, Liu, Xin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.12.2019
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ISSN:2332-7790, 2372-2096
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Shrnutí:The traditional deployment research on wireless sensor networks (WSNs) has mainly focused on 2D plane and 3D full space; also, the sensors considered are almost always omni-directional sensors and are usually homogeneous. However, this type of research cannot fulfill the diverse requirements required for practical 3D environment. We study the deployment problem of heterogeneous directional sensor networks (HDSNs) on 3D terrain, which is more suitable for practical security monitoring requirements and has more practical significance. In this paper, we propose a novel uncertain comprehensive coverage model: a modified 3D directional sensing model is presented, and a non-probabilistic measure based fusion operator is utilized. We transform the deployment problem into a multiobjective optimization problem by comprehensively considering Coverage, Connectivity Uniformity and Deployment Cost, and we use various state-of-the-art multiobjective optimization algorithm based deployment approaches to address it. We conduct deployment experiments on three types of real-world 3D terrain data (plain, hill and mountain). Through the analysis of the deployment results, we obtain a deeper understanding and insight into the multiobjective deployment problem of HDSN. Meanwhile, we more clearly recognize the characteristics of the deployment approaches.
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ISSN:2332-7790
2372-2096
DOI:10.1109/TBDATA.2017.2685581