Large-scale Underwater Wireless Sensor Networks Research Articles

Hierarchical localization algorithm for sustainable ocean health in large-scale underwater wireless sensor networks

Being an extensive part of marine study, underwater localization has fascinated widespread consideration in both civil and military. The underwater sensor network localization should differ from existing terrestrial and recent localization techniques, owing to catastrophic ocean conditions, large-scale networks, and node drift, even in a static environment, along with the pretense of adverse challenges. To address these technical difficulties, we propose a hierarchical localization approach with anchor and ordinary nodes localized in two phases. First, anchor nodes are localized with the help of surface buoys, drifted on the water. Second, we propose a threshold that originates from the midpoint of the deployed anchor nodes for ordinary node localization. The nature of the threshold in the proposed technique enables the localization of all nodes in a network by demonstrating that the anchor node can cover 100% of the area after the nodes are deployed. Simulation results show that the proposed scheme gains high energy efficiency and precision, as well as wide localization coverage, which helps in ocean sustainability. In addition, the proposed technique is implemented in the Aqua-sim toolkit of NS-2 for the validation of the simulation results.

Scalable asynchronous localization algorithm with mobility prediction for underwater wireless sensor networks

With the exploration of ocean resources, underwater wireless sensor networks have become a new research focus. Localization is one of most important technologies in the application of underwater wireless sensor networks. Because of the complex of underwater environment, it is difficult to realize the precisely synchronous localization in the underwater wireless sensor networks especially the large-scale networks with mobility. To solve this problem, in this paper, we propose a scalable asynchronous localization algorithm with mobility prediction. In this localization algorithm, the large-scale underwater wireless sensor network architecture is designed. Considering the node mobility, the node motion model is built based on the tidal mobility. By analyzing the asynchronous communication between the anchor nodes and ordinary nodes, the initial position of ordinary nodes is obtained and the future position of ordinary nodes is predicted and updated. The precisely located ordinary nodes are upgraded to new reference nodes and the new reference nodes locate the other unknown ordinary nodes together with the anchor nodes until the localization tasks of all ordinary nodes are completed. Simulation results confirm that the proposed localization algorithm can achieve accurate localization of mobile nodes in large-scale underwater wireless sensor networks with asynchronous clock.

Centralized underwater node localization using range based multilateral accumulation method (RBMAM)

In large-scale underwater wireless sensor networks (UWSNs), many methods are proposed to localize underwater nodes for distributed networks. Compared to distributed networks, there are many problems such as large number of nodes, limited communication distances and incapability to cover full networks in centralized networks. Usually we use surface gateway node travelling in a fixed trajectory and simultaneously collecting underwater node information to localize node positions individually. While this method has low efficiency and high-complex operations, which is unsuitable for large-scale underwater node localization. Because of the limited underwater bandwidth, multipath interference and high propagation channels, the methods widely used in wireless localization cannot be directly used underwater. To deal with the typical problems in centralized underwater networks, this paper proposes a range based multilateral accumulation method (RBMAM). The method is designed for large-scale, high-efficiency and high precision underwater networks. We compared the performance with area localization scheme (ALS), which is widely used in wireless localization, and least square method (LSM). Simulation and actual experiment with four nodes are also performed. The results prove that this method has equal localization precision to LSM and high-efficiency, it is the ideal method for large-scale UWSN localization.

The Influence of MAC Protocol on a Non-Synchronous Localization Scheme in Large-Scale UWSNs

Localization plays a more and more important role in underwater wireless sensor networks (UWSNs). But in the large-scale UWSNs, the localization algorithm can’t be realized for the continuous packet collision. Therefore, we need to consider the impact of MAC protocol on the positioning algorithm. First, this paper proposes a multi-layer positioning model based on the underwater network architecture. Then according to the non-synchronous localization scheme, we analyze the reason of packet collisions and propose the variable interval ALOHA (VI-ALOHA) protocol based on the Poisson distribution. The VI-ALOHA protocol reduces the collision by adding random space–time. Through the comparison of localization coverage, packet loss, and localization time, this paper evaluates the impact on the localization result in equal interval ALOHA (EI-ALOHA) and VI-ALOHA. Our simulation results show that the MAC protocol has a significant influence on localization; besides, the localization coverage and the packet loss of VI-ALOHA protocol are above 20% better than the EI-ALOHA.

Topology Control for Diverse Coverage in Underwater Wireless Sensor Networks

Underwater wireless sensor networks (UWSNs) have been developed for a set of underwater applications, including the resource exploration, pollution monitoring, tactical surveillance, and so on. However, the complexity and diversity of the underwater environment differentiate it significantly from the terrestrial environment. In particular, the coverage requirements (i.e., coverage degrees and coverage probabilities) at different regions probably differ underwater. Nevertheless, little effort has been made so far on the topology control of UWSNs given the diverse coverage requirements. To this end, this article proposes two algorithms for the diverse coverage problem in UWSNs: (1) Traversal Algorithm for Diverse Coverage (TADC), which adjusts the sensing radii of nodes successively, that is, at each round only one node alters its sensing radius, and (2) Radius Increment Algorithm for Diverse Coverage (RIADC), which sets the sensing radii of nodes incrementally, that is, at each round multiple nodes may increase their sensing radii simultaneously. The performances of TADC and RIADC are analyzed through mathematical analysis and simulations. The results reveal that both TADC and RIADC can achieve the diverse coverage while minimizing the energy consumption. Moreover, TADC and RIADC perform nicely in obtaining optimal sensing radii and reducing message complexity, respectively. Such merits further indicate that TADC and RIADC are suitable for small-scale and large-scale UWSNs, respectively.

Orthogonal Regression Based Multihop Localization Algorithm for Large-Scale Underwater Wireless Sensor Networks

For large-scale underwater wireless sensor networks (UWSNs) with a minority of anchor nodes, multihop localization is a popular scheme for determining the geographical positions of normal nodes. However, existing multihop localization studies have considered the anchor positions to be free of errors, which is not a valid assumption in practice. In this paper, the problems existing in nonlinear least square-based node self-localization schemes are analyzed, and the biased distribution characteristic of multihop distance estimation errors is pointed out. Then, the orthogonal regression method is employed for the localization of normal nodes in the presence of anchor position errors. In particular, the influences of errors in independent variables and biases in dependent variables on node coordinate estimation are taken into account simultaneously. Extensive simulation results illustrate the robustness and effectiveness of our method.

Set-Membership Adaptive Localization Algorithm with Time-Varying Error Bounds for Underwater Wireless Sensor Networks

This paper presents a set-membership adaptive localization algorithm with time-varying error bounds for underwater wireless sensor networks (UWSNs). In large-scale UWSNs, the nonstationary underwater environments, the insufficient prior information of hybrid noise, the small sample size of available distance measurements, and the node mobility all pose severe challenges for localization, and most current schemes are not applicable. Unlike most of the existing approaches, we tackle the multihop localization problem in a set-membership framework based on the consideration that the distance measurement uncertainty can be cast into an unknown but bounded (UBB) context. The principle of our scheme is firstly to use the bootstrap method to build confidence intervals and error bounds from a small sample set of distance measurements and then to determine the positions by a low-complexity interval analysis method as well as an adaptive localization update specification with time-varying error bounds. Simulation results show that our proposed scheme is an effective and efficient localization approach in large-scale UWSNs.

Set‐membership localisation algorithm based on adaptive error bounds for large‐scale underwater wireless sensor networks

Proposed is a new set-membership approach based on adaptive error bounds to solve multi-hop localisation problems in the cases where the prior information is insufficient and only a very few distance measurements are available, which are commonly encountered in large-scale underwater wireless sensor networks. Unlike most of the existing schemes, the localisation problem is solved in a set-membership framework which is based on the consideration that the distance measurement uncertainty can be cast into an unknown but bounded context. For the first time, an adaptive bounds specification is introduced into multi-hop localisation for eliminating the risk of overbounding or underbounding. To reduce the computational burden, boxes are utilised to approximate the irregular intersection of all feasible solutions. Then the feasible sets and coordinates of ordinary nodes are obtained by using the interval analysis method. Simulation results confirm the effectiveness of the algorithm.

Multi-hop Localization Algorithm for Large-scale Underwater Wireless Sensor Networks

Multi-hop Localization Algorithm for Large-scale Underwater Wireless Sensor Networks