An Enhanced Virtual Force Algorithm for Diverse k-Coverage Deployment of 3D Underwater Wireless Sensor Networks

Abstract

The combination of Wireless Sensor Networks (WSNs) and edge computing not only enhances their capabilities, but also motivates a series of new applications. As a typical application, 3D Underwater Wireless Sensor Networks (UWSNs) have become a hot research issue. However, the coverage of underwater sensor networks problem must be solved, for it has a great significance for the network’s capacity for information acquisition and environment perception, as well as its survivability. In this paper, we firstly study the minimal number of sensor nodes needed to build a diverse k-coverage sensor network. We then propose a k-Equivalent Radius enhanced Virtual Force Algorithm (called k-ERVFA) to achieve an uneven regional coverage optimization for different k-coverage requirements. Theoretical analysis and simulation experiments are carried out to demonstrate the effectiveness of our proposed algorithm. The detailed performance comparisons show that k-ERVFA acquires a better coverage rate in high k-coverage sub-regions, thus achieving a desirable diverse k-coverage deployment. Finally, we perform sensitivity analysis of the simulation parameters and extend k-ERVFA to special cases such as sensor-sparse regions and time-variant situations.

An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

“…As mentioned above, in recent years, research on UWSNs mainly involves topics like node deployment [ 7 , 8 , 9 , 10 ], node localization [ 11 ], network protocol design [ 3 , 12 ], simulation [ 13 , 14 , 15 ], etc. Specially, the issue of node deployment has attracted attention from lots of scholars and engineers.…”

“…In recent years, acoustic-based UWSNs have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc [4][5][6]. Research on UWSNs mainly involves node deployment [7][8][9][10], node localization [11], network protocol design [3,12], simulation [13][14][15], etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, which directly affects the performance of networks.…”

A Binary Adaptive Clone Shuffled Frog Leaping Algorithm for Three‐Dimensional Low‐Energy Target Coverage Optimization in Environmental Monitoring Wireless Sensor Networks

“…If sensor monitoring nodes are randomly distributed, to maximize the network survival This article uses a probabilistic perception model. Considering the complexity of the actual application environment, the probabilistic model can more reasonably represent the perception characteristics of sensor nodes [22]. In actual EMWSNs, the various sensing signals of the sensors will attenuate with the increase of the propagation distance, and the sensor nodes deployed in the field will also be interfered with by various environmental noises.…”

Collaborative Neural Network Algorithm for Event-Driven Deployment in Wireless Sensor and Robot Networks

“…For example, the deployment methods of distance measuring sensors, underwater ultrasonic sensors, and camera sensors generally involve deterministic deployment. In [22], the authors propose a k-equivalent radius enhanced virtual force algorithm for achieving an uneven regional coverage optimization for different requirements. In [23], the authors present an optimized strategy in which sensor deployment begins from the center of the target region by adding an external central force to avoid covering holes or unusual structures.…”