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

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3496 ◽  
Author(s):  
Wenming Wang ◽  
Haiping Huang ◽  
Fan He ◽  
Fu Xiao ◽  
Xin Jiang ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Sensor Networks ◽  
Underwater Wireless Sensor Networks ◽  
Typical Application ◽  
Equivalent Radius ◽  
Virtual Force ◽  
Special Cases

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.

A Taxonomy of Routing Techniques in Underwater Wireless Sensor Networks

2012 ◽  
pp. 119-147
Author(s):  
Muhammad Ayaz ◽  
Azween Abdullah ◽  
Ibrahima Faye
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dynamic Environment ◽  
Vital Role ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Sensor Networks ◽  
Underwater Wireless Sensor Networks ◽  
Sea Bed ◽  
Application Requirements

Underwater Wireless Sensor Networks (UWSNs) are finding different applications for offshore exploration and ocean monitoring. In most of these applications, the network consists of a significant number of sensor nodes deployed at different depth levels throughout the area of interest. Sensor nodes on the sea bed cannot communicate directly with the nodes near the surface level, so they require multihop communication assisted by an appropriate routing scheme. However, this appropriateness not only depends on network resources and application requirements, but environment constraints are involved as well. These factors all provide a platform where a resource aware routing strategy plays a vital role in fulfilling different application requirements with dynamic environment conditions. Realizing this fact, much of the attention has been given to construct a reliable scheme, and many routing protocols have been proposed in order to provide efficient route discoveries between the source and sink. In this chapter, the authors present a review and comparison of different algorithms proposed recently for underwater sensor networks. Later on, all of these have been classified into different groups according to their characteristics and functionalities.

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

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1368 ◽  
Author(s):  
Luoheng Yan ◽  
Yuyao He ◽  
Zhongmin Huangfu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Optimization Algorithm ◽  
Growth Ring ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Connected Network ◽  
Deployment Optimization

The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.

scholarly journals A data forwarding algorithm based on Markov thought in underwater wireless sensor networks

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769198
Author(s):  
Dongwei Li ◽  
Jingli Du ◽  
Linfeng Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Success Rate ◽  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Bottom To Top

The underwater wireless sensor networks composed of sensor nodes are deployed underwater for monitoring and gathering submarine data. Since the underwater environment is usually unpredictable, making the nodes move or be damaged easily, such that there are several vital objectives in the data forwarding issue, such as the delivery success rate, the error rate, and the energy consumption. To this end, we propose a data forwarding algorithm based on Markov thought, which logically transforms the underwater three-dimensional deployment model into a two-dimensional model, and thus the nodes are considered to be hierarchically deployed. The data delivery is then achieved through a “bottom to top” forwarding mode, where the delivery success rate is improved and the energy consumption is reduced because the established paths are more stable, and the proposed algorithm is self-adaptive to the dynamic routing loads.

scholarly journals Localization Free Energy Efficient and Cooperative Routing Protocols for Underwater Wireless Sensor Networks

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 498 ◽  
Author(s):  
Sahar Shah ◽  
Anwar Khan ◽  
Ihsan Ali ◽  
Kwang-Man Ko ◽  
Hasan Mahmood
Keyword(s):  
Wireless Sensor Networks ◽  
Free Energy ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Cooperative Routing

Mitigation of channel unfavorable circumstances during data routing in underwater wireless sensor networks (UWSNs) has utmost significance. It guarantees saving packet corruption along unfavorable channels so that vital data is not lost or become meaningless. This paper proposes two routing protocols for UWSNs: localization free energy efficient routing (LFEER) and its improved version, localization free energy efficient cooperative routing (Co-LFEER). The LFEER makes decision of choosing a relay based on its maximum residual energy, number of hops and the bit error rate of the link over which packets are transmitted. These metrics are chosen to save packets from corruption to the maximum limit and maintain stable paths (where nodes do not die soon). Since a single link is used in the LFEER for packets forwarding, the link may become worse with changing circumstances of the channel. To deal with this issue, cooperative routing is added to the LFFER to construct the Co-LFEER protocol, in which some copies of packets are received by destination to decide about packets quality. Converse to some prevalent protocols, both LFEER and Co-LFEER are independent of knowing the sensor nodes’ positions, which increases computational complexity and wasteful utilization of resources. Based on extensive simulations, the proposed schemes are better than Co-DBR in reducing energy utilization and advancing packets to the desired destination.

scholarly journals Cooperative, reliable, and stability-aware routing for underwater wireless sensor networks

2019 ◽  
Vol 15 (6) ◽  
pp. 155014771985424 ◽  
Author(s):  
Munsif Ali ◽  
Anwar Khan ◽  
Hasan Mahmood ◽  
Naeeem Bhatti
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Depth Sensor ◽  
Data Packets ◽  
Final Destination ◽  
Cooperative Routing ◽  
Channel Effects

In underwater wireless sensor networks, stability and reliability of the network are of paramount importance. Stability of the network ensures persistent operation of the network that, in consequence, avoids data loss when nodes consume all the battery power and subject to death. Particularly, nodes bearing a low pressure of water die early in the usual routing approach due to being preferred choices for data routing. Reliability ensures minimization of the adverse channel effects on data packets so that the desired information is easily extracted from these packets. This article proposes two routing protocols for underwater wireless sensor networks: reliable and stability-aware routing and cooperative reliable and stability-aware routing. In reliable and stability-aware routing, energy assignment to a node is made on the basis of its depth. Sensor nodes having the lowest depth are assigned the highest amount of energy. This energy assignment is called the energy grade of a node and five energy grades are formed in the proposed network from top to bottom. The energy grade along with energy residing in a node battery and its depth decide its selection as a forwarder node. The reliable and stability-aware routing uses only a single link to forward packets. Such a link may not be reliable always. To overcome this issue, the cooperative reliable and stability-aware routing is proposed which introduces cooperative routing to reliable and stability-aware routing. Cooperative routing involves the reception of multiple copies of data symbols by destination. This minimizes the adverse channel effects on data packets and makes the information extraction convenient and less cumbersome at the final destination. Unlike the conventional approach, the proposed schemes do not take into account the coordinates of nodes for defining the routing trajectories, which is challenging in underwater medium. Simulation results reveal a better behavior of the proposed protocols than some competitive schemes in terms of providing stability to the network, packet transfer to the ultimate destination, and latency.

scholarly journals Reinforcement Learning-Based Data Forwarding in Underwater Wireless Sensor Networks with Passive Mobility

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 256 ◽  
Author(s):  
Haotian Chang ◽  
Jing Feng ◽  
Chaofan Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mobility Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Energy Constrained

Data forwarding for underwater wireless sensor networks has drawn large attention in the past decade. Due to the harsh underwater environments for communication, a major challenge of Underwater Wireless Sensor Networks (UWSNs) is the timeliness. Furthermore, underwater sensor nodes are energy constrained, so network lifetime is another obstruction. Additionally, the passive mobility of underwater sensors causes dynamical topology change of underwater networks. It is significant to consider the timeliness and energy consumption of data forwarding in UWSNs, along with the passive mobility of sensor nodes. In this paper, we first formulate the problem of data forwarding, by jointly considering timeliness and energy consumption under a passive mobility model for underwater wireless sensor networks. We then propose a reinforcement learning-based method for the problem. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate the validity of the proposed method. Our method outperforms the benchmark protocols in both timeliness and energy efficiency. More specifically, our method gains 83.35% more value of information and saves up to 75.21% energy compared with a classic lifetime-extended routing protocol (QELAR).

Trust Management for One-Hop Cluster-Based Underwater Wireless Sensor Networks

2012 ◽  
Vol 488-489 ◽  
pp. 1163-1167
Author(s):  
Yan Ping Cong ◽  
Zhi Qiang Wei ◽  
Guang Yang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Trust Management ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Management Problem ◽  
Underwater Wireless Sensor Networks ◽  
Management Scheme ◽  
Trust Management Scheme ◽  
Current Movement

In this paper, we studied the trust management problem in one-hop cluster-based underwater wireless sensor networks (UWSNs). Trust plays an important role in constructing UWSNs. Due to the dynamic natures of UWSNs (current movement, addition or deletion of nodes) and the massive deployment of underwater sensor nodes, coupled with the short range of water acoustic communications, we need to ensure that all communicating nodes are trusted. We propose a hierarchical trust management scheme for one-hop cluster-based underwater wireless sensor networks.

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