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Collaborative Neural Network Algorithm for Event-Driven Deployment in Wireless Sensor and Robot Networks
- Source :
- Sensors, Vol 20, Iss 10, p 2779 (2020)
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- Wireless sensor and robot networks (WSRNs) often work in complex and dangerous environments that are subject to many constraints. For obtaining a better monitoring performance, it is necessary to deploy different types of sensors for various complex environments and constraints. The traditional event-driven deployment algorithm is only applicable to a single type of monitoring scenario, so cannot effectively adapt to different types of monitoring scenarios at the same time. In this paper, a multi-constrained event-driven deployment model is proposed based on the maximum entropy function, which transforms the complex event-driven deployment problem into two continuously differentiable single-objective sub-problems. Then, a collaborative neural network (CONN) event-driven deployment algorithm is proposed based on neural network methods. The CONN event-driven deployment algorithm effectively solves the problem that it is difficult to obtain a large amount of sensor data and environmental information in a complex and dangerous monitoring environment. Unlike traditional deployment methods, the CONN algorithm can adaptively provide an optimal deployment solution for a variety of complex monitoring environments. This greatly reduces the time and cost involved in adapting to different monitoring environments. Finally, a large number of experiments verify the performance of the CONN algorithm, which can be adapted to a variety of complex application scenarios.
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 20
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Sensors
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.52aaa5281f2476d9d0f6f9759ae07af
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/s20102779