Coverage Control Algorithm-Based Adaptive Particle Swarm Optimization and Node Sleeping in Wireless Multimedia Sensor Networks

Wireless multimedia sensor networks (WMSNs) are widely used in various fields where coverage control is a critical difficulty because multiple requirements need to be considered such as service quality and energy consumption. In this paper, we focus on the issues existing in coverage model and cover...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.170096-170105
Main Authors: Jiao, Zhenghua, Zhang, Lei, Xu, Miao, Cai, Changxin, Xiong, Jie
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive algorithms
Adaptive control
Control algorithms
Control methods
Control theory
coverage control
Energy consumption
location optimization
Mathematical model
Multimedia
node sleeping
Optimization
Particle swarm optimization
Robot sensing systems
Sensors
Solid modeling
Three dimensional models
Wireless multimedia sensor networks
Wireless networks
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Summary:Wireless multimedia sensor networks (WMSNs) are widely used in various fields where coverage control is a critical difficulty because multiple requirements need to be considered such as service quality and energy consumption. In this paper, we focus on the issues existing in coverage model and coverage control method, and propose an adaptive particle swarm optimization algorithm for solving the coverage control problem in the WMSNs. First of all, a 3D coverage model is developed with introducing the perceptual radius of sensors, while the optimal projection area of a single sensor is deduced. Hereafter, an adaptive particle swarm optimization is suggested to optimize the location information of sensors for reducing both perceptual overlapping areas and perceptual blind areas in the monitoring area. At last, a redundant node y is presented to reduce the number of working sensors. Simulation results have show that we can ensure better coverage as well as fewer sensors compared to the state-of-the-art frameworks.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2954356