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Cao, B, Kang, X, Zhao, J, Yang, P, Lv, Z and Liu, X (2018) Differential Evolution-based 3D Directional Wireless Sensor Network Deployment Optimization. IEEE Internet of Things, 5 (5). pp. 3594-3605. ISSN 2327-4662
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Abstract
Wireless sensor networks (WSNs) are applied more and more widely in real life. In actual scenarios, 3D directional wireless sensors (DWSs) are constantly employed, thus, research on the real-time deployment optimization problem of 3D directional wireless sensor networks (DWSNs) based on terrain big data has more practical significance. Based on this, we study the deployment optimization problem of DWSNs in the 3D terrain through comprehensive consideration of coverage, lifetime, connectivity of sensor nodes, connectivity of cluster headers and reliability of DWSNs. We propose a modified differential evolution (DE) algorithm by adopting CR-sort and polynomial-based mutation on the basis of the cooperative coevolutionary (CC) framework, and apply it to address deployment problem of 3D DWSNs. In addition, to reduce computation time, we realize implementation of message passing interface (MPI) parallelism. As is revealed by the experimentation results, the modified algorithm proposed in this paper achieves satisfying performance with respect to either optimization results or operation time.
| Item Type: | Article |
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| Additional Information: | (c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Institute of Electrical and Electronics Engineers |
| Date Deposited: | 17 Jan 2018 10:25 |
| Last Modified: | 04 Sep 2021 10:51 |
| DOI or ID number: | 10.1109/JIOT.2018.2801623 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/7866 |
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