Three-dimensional Underwater Sensor Networks Research Articles

Node Deployment Strategy Based on Improved Particle Swarm Algorithm in Three-dimensional Underwater Sensor Networks

To enhance the monitoring quality of the underwater three-dimensional target area and address issues such as uneven node distribution, inadequate coverage, and poor connectivity in traditional deployment strategies, a new node deployment strategy based on grid deployment with a variable weight particle swarm algorithm has been proposed in this research paper. Its goal is to minimize the quantity of deployed nodes while maintaining the coverage and connectivity of the three-dimensional wireless sensor networks (UWSNs). Simulation results demonstrate that this deployment strategy leads to good performance of the sensor network, and our approach ensures maximum coverage with the same number of nodes.

Robust and Cooperative Localization for Underwater Sensor Networks in the Existence of Malicious Anchors.

Precise and robust localization in three-dimensional underwater sensor networks is still an important research problem. This problem is particularly challenging if there are some malicious anchors among ordinary anchor nodes that will broadcast their locations falsely and deliberately. In this paper, we study how to self-localize large teams of underwater sensor nodes under the condition that some malicious anchor nodes mixed with ordinary anchors. Due to malicious characteristic of some deliberate anchor nodes, an iterative and cooperative 3D-localization algorithm for underwater sensor networks in the existence of malicious anchors is proposed in this paper. The proposed robust localization algorithm takes advantage of distributed reputation voting method within 1-Hop neighboring reference nodes to detect and eliminate malicious anchor nodes. Moreover, one kind of Minimum Mean Squared Error estimation based iterative localization method is applied to determine accurate location information. Additionally, we analyze and prove that our localization algorithm would have a bounded error when the number of malicious anchors is smaller than a certain threshold. Extensive simulation results are provided to demonstrate performance improvements comparing to traditional Minimum Mean Squared Error and Attack Resistant Minimum Mean Squared Error based localization methods in terms of localization accuracy and coverage ratio.

Underwater Wireless Sensor Networks Challenges: A Review

The underwater wireless sensor network consists of sensors that enable the exploration of natural undersea resources and gathering scientific data in collaborative monitoring missions. Underwater wireless sensor Network consists of variable number of floating and anchored sensors, sink and vehicles that are deployed over an area to be explored. Applications of underwater sensing range from oil industry to aquaculture, and include instrument monitoring, pollution control, climate recording, Prediction of natural disturbances, search and survey missions, and study of marine life. UWSN is a network of autonomous sensor nodes. Which are spatially distributed underwater to sense the water-related properties such as quality, temperature, and pressure? The sensed data can be utilized by variety of applications that can be used for the benefit of humans. The sensor nodes, stationary or mobile are connected wirelessly via communication modules to transfer various events of interest. In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the underwater channel is characterized. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed at all layers of the protocol stack. Furthermore, open research issues are discussed and possible solution approaches are outlined.

An Energy-Efficient Routing Algorithm in Three-Dimensional Underwater Sensor Networks Based on Compressed Sensing

Compressed sensing (CS) has become a powerful tool to process data that is correlated in underwater sensor networks (USNs). Based on CS, certain signals can be recovered from a relatively small number of random linear projections. Since the battery-driven sensor nodes work in adverse environments, energy-efficient routing well-matched with CS is needed to realize data gathering in USNs. In this paper, a clustering, uneven-layered, and multi-hop routing based on CS (CS-CULM) is proposed. The inter-cluster transmission and fusion are fulfilled by an improved LEACH protocol, then the uneven-layered, multi-hop routing is adopted to forward the packets fused to sink node for data reconstruction. Simulation results show that CS-CULM can achieve better performances in energy saving and data reconstruction.

3D Dubins curves based path programming for mobile sink in underwater sensor networks

Mobile data collection is one of research highlights for sparse three-dimensional underwater sensor networks. Therein, optimal or near-optimal cruise trajectory planning of mobile sink is very crucial. A 3D Dubins curves based continuous path programming algorithm (GA-3DTSP in short) for underwater mobile sink with non-holonomic constraints such as well-known autonomous underwater vehicle is proposed. The objective of GA-3DTSP algorithm is to trace sparsely deployed sensor nodes by mobile sink so as to achieve near-optimal energy conservation efficiency. First, an extended 3D Dubins curve is proposed and the length calculation formulae for 3D Dubins curve are investigated. Furthermore, genetic algorithm is used to tackle this difficult NP-complete problem of planning shortest paths in a heuristic manner. Finally, simulation results verify that the proposed GA-3DTSP method can conserve cruise energy of mobile sink effectively.

Redundancy Model and Boundary Effects Based Coverage-Enhancing Algorithm for 3D Underwater Sensor Networks

In the study of three-dimensional underwater sensor networks, the nodes would produce changes in perception range under the influence of environmental factors and their own hardware. Requesting all nodes completely isomorphic is unrealistic. Ignoring boundary effects usually causes the coverage effect of the actual deployment of networks to not reach the anticipated result. This paper firstly presents an underwater sensing model with normal distributed node sensing radius. Secondly, it gives the relationship between expected deployment quality and the number of nodes in the premise of considering boundary effects. Then, it deduces nodes’ redundancy formula based on the sensing model with normal distributed node sensing radius, making node could determine whether itself is a redundant node only based on the number of its neighbour nodes. Furthermore, this paper proposes a redundancy model and boundary effects based coverage-enhancing algorithm for three-dimensional underwater sensor networks (RBCT). Simulation results show that RBCT, compared to similar algorithms, has certain advantages in saving energy and enhancing coverage rate.

An Efficient Coverage Control Algorithm for Three-dimensional Underwater Sensor Networks

An Efficient Coverage Control Algorithm for Three-dimensional Underwater Sensor Networks

State of the art in protocol research for underwater acoustic sensor networks

Underwater networks of sensors have the potential to enable unexplored applications and to enhance our ability to observe and predict the ocean. In this paper, architectures for two-dimensional and three-dimensional underwater sensor networks are proposed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols is given and open research issues are discussed.

Underwater acoustic sensor networks: research challenges

Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined.

Challenges for efficient communication in underwater acoustic sensor networks

Ocean bottom sensor nodes can be used for oceanographic data collection, pollution monitoring, offshore exploration and tactical surveillance applications. Moreover, Unmanned or Autonomous Underwater Vehicles (UUVs, AUVs), equipped with sensors, will find application in exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater Networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area.In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the underwater channel is characterized. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed at all layers of the protocol stack. Furthermore, open research issues are discussed and possible solution approaches are outlined.