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3D deployment optimization for Heterogeneous Wireless Directional Sensor Networks on Smart City

Yang, P, Cao, B, Zhao, J, Liu, X and Zhang, Y (2018) 3D deployment optimization for Heterogeneous Wireless Directional Sensor Networks on Smart City. IEEE Transactions on Industrial Informatics. ISSN 1941-0050

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Abstract

The development of smart cities and the emergence of 3D urban terrain data have introduced new requirements and issues to the research of wireless sensor network (WSN) 3D deployment. In this paper, we study the deployment issue of heterogeneous wireless directional sensor networks (HWDSNs) on 3D smart cities. Traditionally, studies about the deployment problem of WSNs show solicitude for omni-directional sensors on 2D plane or in 3D full space. As WSNs exist in complex 3D environments and directional sensors are emerging, the work of this paper will have more practical significance. Based on the 3D urban terrain data, we transform the deployment problem into a multiobjective optimization problem (MOP), in which objectives of Coverage, Connectivity Quality and Lifetime, as well as the Connectivity and Reliability constraints are simultaneously given close attention to. A graph-based 3D signal propagation model employing the line-of-sight (LOS) concept is used to calculate the signal path loss. The novel distributed parallel multiobjective evolutionary algorithms (MOEAs) are proposed. For verification, a real-world and an artificial urban terrains are utilized. Compared with other state-of-the-art MOEAs, the novel algorithms address the deployment problem more effectively and more efficiently in terms of optimization

Item Type: Article
Additional Information: © 2018 IEEE
Uncontrolled Keywords: 08 Information And Computing Sciences, 09 Engineering, 10 Technology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science
Publisher: Institute of Electrical and Electronics Engineers
Date Deposited: 07 Nov 2018 11:47
Last Modified: 05 Feb 2019 11:08
DOI or Identification number: 10.1109/TII.2018.2884951
URI: http://researchonline.ljmu.ac.uk/id/eprint/9620

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