Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Localization of Underwater Sensor Networks for Ranging Interference based on the AdaDelta Gradient Descent Algorithm

View through CrossRef
Abstract The precise localization of sensor nodes is a key link in underwater wireless sensor networks (UWSNs) applications. Furthermore, the nodes in UWSNs should be able to independently determine their relative positions before they begin to receive and transmit data to each other. Most of the existing underwater localization algorithms are based on the anchor nodes with known locations, and the rest of the nodes can be calculated by the anchor nodes. The iterative localization process has been proposed for the localization of UWSNs, in which some positioned nodes as reference nodes are selected for iterative localization. However, in real scenarios, some anchor nodes may be destroyed naturally or artificially damaged or even used to convey misleading information to interfere with the precise localization of other nodes underwater. This paper proposes a computationally efficient localization algorithm that can accurately locate the sensor nodes underwater to resist such network attacks. The proposed algorithm achieves better localization accuracy by iteratively removing misleading information transmitted from interfering nodes based on the Time Difference of Arrival ranging mapping and combining selective minimum gradient of AdaDelta gradient descent (AGD). The simulation results prove that the proposed algorithm performs better under network attacks than the existing algorithms.
Title: Localization of Underwater Sensor Networks for Ranging Interference based on the AdaDelta Gradient Descent Algorithm
Description:
Abstract The precise localization of sensor nodes is a key link in underwater wireless sensor networks (UWSNs) applications.
Furthermore, the nodes in UWSNs should be able to independently determine their relative positions before they begin to receive and transmit data to each other.
Most of the existing underwater localization algorithms are based on the anchor nodes with known locations, and the rest of the nodes can be calculated by the anchor nodes.
The iterative localization process has been proposed for the localization of UWSNs, in which some positioned nodes as reference nodes are selected for iterative localization.
However, in real scenarios, some anchor nodes may be destroyed naturally or artificially damaged or even used to convey misleading information to interfere with the precise localization of other nodes underwater.
This paper proposes a computationally efficient localization algorithm that can accurately locate the sensor nodes underwater to resist such network attacks.
The proposed algorithm achieves better localization accuracy by iteratively removing misleading information transmitted from interfering nodes based on the Time Difference of Arrival ranging mapping and combining selective minimum gradient of AdaDelta gradient descent (AGD).
The simulation results prove that the proposed algorithm performs better under network attacks than the existing algorithms.

Related Results

Dynamic stochastic modeling for inertial sensors
Dynamic stochastic modeling for inertial sensors
Es ampliamente conocido que los modelos de error para sensores inerciales tienen dos componentes: El primero es un componente determinista que normalmente es calibrado por el fabri...
Indoor Localization System Based on RSSI-APIT Algorithm
Indoor Localization System Based on RSSI-APIT Algorithm
An indoor localization system based on the RSSI-APIT algorithm is designed in this study. Integrated RSSI (received signal strength indication) and non-ranging APIT (approximate pe...
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies are revolutionizing the way we explore and understand the underwater world. This review examines the latest advancements in underwater surve...
Optimizing Underwater Vision: A Rigorous Investigation into CNN's Deep Image Enhancement for Subaquatic Scenes
Optimizing Underwater Vision: A Rigorous Investigation into CNN's Deep Image Enhancement for Subaquatic Scenes
In this paper, Convolutional Neural Networks were used to enhance the visual fidelity of underwater images. The UWCNN is introduced in this article, which utilizes underwater scene...
Anchor Nodes Placement for Effective Passive Localization
Anchor Nodes Placement for Effective Passive Localization
Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but n...
Edge Enhanced CrackNet for Underwater Crack Detection of Concrete Dams
Edge Enhanced CrackNet for Underwater Crack Detection of Concrete Dams
Underwater crack detection in dam structures is of significant engineering importance and scientific value for ensuring the structural safety, assessing operational conditions, and...
Wireless Sensor Networks Node Localization Algorithm Based on Range Optimization and Graph Optimization
Wireless Sensor Networks Node Localization Algorithm Based on Range Optimization and Graph Optimization
<p>To address the problem of low localization accuracy in the node localization algorithms of wireless sensor networks (WSN) based on received signal strength indication (RSS...
Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks
Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks
Energy efficiency has always been a hot issue in wireless sensor networks. A lot of energy-efficient algorithms have been proposed to reduce energy consumption in traditional wirel...

Back to Top