A Voronoi-Based Depth-Adjustment Scheme for Underwater Wireless Sensor Networks

Wu, Jiagao; Wang, Yinan; Liu, Linfeng

doi:10.21307/ijssis-2017-538

Cited by 13 publications

(9 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, some scholars have transferred the concept of computational geometry deployment strategies to UWSN applications. Wu et al [ 24 ] proposed Voronoi-based depth-adjustment algorithm (VBDA) for UWSNs. First, all of the nodes are randomly deployed on the water surface through the formation of the Voronoi polygon of each node to calculate the network coverage redundancy, the Voronoi region area of each node in same layer to determine the depth-adjustment distance, and then the iterative operating process of depth adjustment until the last layer network deployment arrives at the water bottom threshold.…”

Section: Introductionmentioning

confidence: 99%

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

Jiang

Liu

et al. 2016

Sensors

View full text Add to dashboard Cite

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

show abstract

Section: Introductionmentioning

confidence: 99%

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

Jiang

Liu

et al. 2016

Sensors

View full text Add to dashboard Cite

show abstract

“…Two other approaches for adjusting nodes position that are randomly deployed on the surface of the ocean are presented in [20], [21]. Both approaches implementing Voronoi Diagram to adjust the nodes position based on the density of sensor nodes.…”

Section: A Self-depth Adjustment Techniquementioning

confidence: 99%

Deployment Protocol for Underwater Wireless Sensors Network based on Virtual Force

Almutairi¹,

Mahfoudh²

2017

ijacsa

View full text Add to dashboard Cite

Abstract-Recently, Underwater Sensor Networks (UWSNs) have attracted researchers' attention due to the challenges and the peculiar characteristics of the underwater environment. The initial random deployment of UWSN where sensors are scattered over the area via planes or ships is inefficient, and it doesn't achieve full coverage nor maintain network connectivity. Moreover, energy efficiency in underwater networks is a crucial issue since nodes utilize battery power as a source of energy and it is difficult and sometimes impossible to change or replenish these batteries. Our contribution in this research is to improve the performance of UWSNs by designing UW-DVFA, an underwater 3-D self-distributed deployment algorithm based on virtual forces. The main target for this work is to stretch the randomly deployed network in the 3-D area in a way that guarantees full area coverage and network connectivity.

show abstract

“…However, this algorithm also adds many difficulties for artificial deployment to poor monitoring aquatic environments, thus increasing high deployment costs. Second, in self-adjustment deployment [28,29,30], the node can only move in a vertical direction by adjusting the length of the anchor rope. This kind of algorithm increases the network coverage area or decreases the coverage overlap by adjusting the depth of the node.…”

Section: Related Workmentioning

confidence: 99%

A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

Shu

Liu

Jiang

2016

Sensors

View full text Add to dashboard Cite

Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs) usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.

show abstract

A Voronoi-Based Depth-Adjustment Scheme for Underwater Wireless Sensor Networks

Cited by 13 publications

References 12 publications

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

Deployment Protocol for Underwater Wireless Sensors Network based on Virtual Force

A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

Contact Info

Product

Resources

About