An Energy Efficiency Node Scheduling Model for Spatial-Temporal Coverage Optimization in 3D Directional Sensor Networks

Han, Chong; Sun, Lijuan; Xiao, Fu; Jian, Guo

doi:10.1109/access.2016.2592184

Cited by 18 publications

(7 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [13,18,19], the authors have better solved the problem of mobile energy consumption, but these are based on 2D plane verification and are not suitable for 3D environments. Therefore, the research of the literature [20][21][22] has successively proposed the orientation sensor model and algorithm for the 3D coordinate system. For example, the authors studied the low-power green communication of 3D DSNs and proposed the space-time coverage optimisation scheduling (STCOS) algorithm to obtain the maximum network coverage in [21].…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, the research of the literature [20][21][22] has successively proposed the orientation sensor model and algorithm for the 3D coordinate system. For example, the authors studied the low-power green communication of 3D DSNs and proposed the space-time coverage optimisation scheduling (STCOS) algorithm to obtain the maximum network coverage in [21]. In [22], the authors propose a network coverage enhancement algorithm based on an artificial fish swarm algorithm to improve the coverage rate.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

2019

View full text Add to dashboard Cite

In directional sensor networks research, target event detection is currently an active research area, with applications in underwater target monitoring, forest fire warnings, border areas, and other important activities. Previous studies have often discussed target coverage in two-dimensional sensor networks, but these studies cannot be extensively applied to three-dimensional networks. Additionally, most of the previous target coverage detection models are based on a circular or omnidirectional sensing model. More importantly, if the directional sensor network does not design a better coverage algorithm in the coverage-monitoring process, its nodes’ energy consumption will increase and the network lifetime will be significantly shortened. With the objective of addressing three-dimensional target coverage in applications, this study proposes a dynamic adjustment optimisation algorithm for three-dimensional directional sensor networks based on a spherical sector coverage model, which improves the lifetime and coverage ratio of the network. First, we redefine the directional nodes’ sensing model and use the three-dimensional Voronoi method to divide the regions where the nodes are located. Then, we introduce a correlation force between the target and the sensor node to optimise the algorithm’s coverage mechanism, so that the sensor node can accurately move to the specified position for target coverage. Finally, by verifying the feasibility and accuracy of the proposed algorithm, the simulation experiments demonstrate that the proposed algorithm can effectively improve the network coverage and node utilisation.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

2019

View full text Add to dashboard Cite

show abstract

“…Sensor coverage, one of the fundamental problems of sensor networks, tries to answer the questions about the quality of sensing (surveillance) that a particular sensor networks provides [ 15 ]. Depending on the type of application, coverage problems can be divided into point coverage [ 5 ], area coverage [ 16 ], and barrier coverage [ 17 ]. A major goal is to detect intruders as they cross a border or as they penetrate a protected area.…”

Section: Related Workmentioning

confidence: 99%

Barrier Coverage for 3D Camera Sensor Networks

Zhang

et al. 2017

Sensors

View full text Add to dashboard Cite

Barrier coverage, an important research area with respect to camera sensor networks, consists of a number of camera sensors to detect intruders that pass through the barrier area. Existing works on barrier coverage such as local face-view barrier coverage and full-view barrier coverage typically assume that each intruder is considered as a point. However, the crucial feature (e.g., size) of the intruder should be taken into account in the real-world applications. In this paper, we propose a realistic resolution criterion based on a three-dimensional (3D) sensing model of a camera sensor for capturing the intruder’s face. Based on the new resolution criterion, we study the barrier coverage of a feasible deployment strategy in camera sensor networks. Performance results demonstrate that our barrier coverage with more practical considerations is capable of providing a desirable surveillance level. Moreover, compared with local face-view barrier coverage and full-view barrier coverage, our barrier coverage is more reasonable and closer to reality. To the best of our knowledge, our work is the first to propose barrier coverage for 3D camera sensor networks.

show abstract

“…WMSNs perceive various media information in the surrounding environment through multimedia sensor nodes. This information can be transmitted to the collection nodes via single and multihop relay [9,10]. Collection nodes analyze and process the received data and send the analysis and processing results to the network owner to realize comprehensive and effective environmental monitoring.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Image Compression Scheme for Energy Harvesting Wireless Multimedia Sensor Networks

Han

Zhang

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

As an emerging technology, edge computing will enable traditional sensor networks to be effective and motivate a series of new applications. Meanwhile, limited battery power directly affects the performance and survival time of sensor networks. As an extension application for traditional sensor networks, the energy consumption of Wireless Multimedia Sensor Networks (WMSNs) is more prominent. For the image compression and transmission in WMSNs, consider using solar energy as the replenishment of node energy; a distributed image compression scheme based on solar energy harvesting is proposed. Two level clustering management is adopted. The camera node-normal node cluster enables camera nodes to gather and send collected raw images to the corresponding normal nodes for compression, and the normal node cluster enables the normal nodes to send the compressed images to the corresponding cluster head node. The re-clustering and dynamic adjustment methods for normal nodes are proposed to adjust adaptively the operation mode in the working chain. Simulation results show that the proposed distributed image compression scheme can effectively balance the energy consumption of the network. Compared with the existing image transmission schemes, the proposed scheme can transmit more and higher quality images and ensure the survival of the network.

show abstract

An Energy Efficiency Node Scheduling Model for Spatial-Temporal Coverage Optimization in 3D Directional Sensor Networks

Cited by 18 publications

References 24 publications

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

Dynamic Adjustment Optimisation Algorithm in 3D Directional Sensor Networks Based on Spherical Sector Coverage Models

Barrier Coverage for 3D Camera Sensor Networks

A Distributed Image Compression Scheme for Energy Harvesting Wireless Multimedia Sensor Networks

Contact Info

Product

Resources

About