scholarly journals A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 156 ◽  
Author(s):  
Wenbo Zhang ◽  
Jing Wang ◽  
Guangjie Han ◽  
Xinyue Zhang ◽  
Yongxin Feng
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Topology Control ◽  
Scheduling Algorithm ◽  
Basic Unit ◽  
Underwater Sensor Networks ◽  
Efficient Operation ◽  
Underwater Sensor Network ◽  
Temporary Control ◽  
3D Topology

3D topology control in underwater sensor networks is of great significance to ensuring reliable and efficient operation of the network. In this paper, by analyzing the characteristics of an underwater sensor network, we take the cube as the basic unit to perform 3D partition of the monitoring area, define the 3D partition unit and basic cluster structure of the underwater sensor network, and arrange rotating temporary control nodes in the cluster. Then, a cluster sleep-wake scheduling algorithm is proposed that compares the remaining node energy. It selects the node with the largest remaining energy as the working node, and the remaining nodes complete the transition of dormancy and waiting states as long as they reach the preset dormancy time. The node state settings of this phase are completed by the temporary control node. Temporary control nodes selecting and sleep-wake scheduling are used in the algorithm through 3D topology control, which reduces energy consumption and guarantees maximum sensing coverage of the entire network and the connection rate of active nodes. Simulation results further verify the effectiveness of the proposed algorithm.

Efficient Node Deployment Algorithm for Enhancing Connectivity and Coverage in Underwater Sensor Networks

2019 ◽  
Vol 17 (12) ◽  
pp. 947-954
Author(s):  
Kamal Kumar Gola ◽  
Bhumika Gupta
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Water Surface ◽  
Area Coverage ◽  
Underwater Sensor Networks ◽  
Node Deployment ◽  
Underwater Sensor Network ◽  
Surface Station ◽  
Coverage And Connectivity ◽  
2D Network

As deployment process is one of the major tasks in underwater sensor network due to its constraint like: acoustic communication, energy, processing speed, cost and memory and dynamic nature of water. As many researchers have proposed many algorithms for the deployment of nodes in underwater sensor network. It was always a great issue in WSN as well as underwater sensor networks. This work proposes a node deployment technique based on depth. This work consists the following major components: (i) sensor nodes to sense the phenomena in underwater sensor networks, (ii) multiple surface station on the water surface. Use of multiple surface station provides better area coverage and connectivity in the networks. This work is divided into three phase like: initialization where nodes are randomly deployed at water surface and from 2D network topology, second phase is depth calculation for all the nodes and third is to distribute the depth to each node and send them to their designated depth to expand the 2D network into the 3D network. The proposed technique is simulated on Matlab for the analysis of area coverage and connectivity. Simulation results show better performance in terms of area coverage and connectivity as compared to ADAN-BC.

scholarly journals Topology Control for Energy-Efficient Localization in Mobile Underwater Sensor Networks Using Stackelberg Game

2019 ◽  
Vol 68 (2) ◽  
pp. 1487-1500 ◽  
Author(s):  
Yali Yuan ◽  
Chencheng Liang ◽  
Megumi Kaneko ◽  
Xu Chen ◽  
Dieter Hogrefe
Keyword(s):  
Sensor Networks ◽  
Energy Efficient ◽  
Topology Control ◽  
Stackelberg Game ◽  
Underwater Sensor Networks

A DEPLOYMENT ALGORITHM FOR UNDERWATER SENSOR NETWORKS IN OCEAN ENVIRONMENT

2011 ◽  
Vol 20 (06) ◽  
pp. 1051-1066 ◽  
Author(s):  
LINFENG LIU
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Wireless Sensor ◽  
Underwater Sensor Networks ◽  
Cluster Shape ◽  
Simulation Results ◽  
Ocean Environment ◽  
Near Future

Underwater sensor networks will find many oceanic applications in near future, and the deployment problem in 3D sensor networks has not been paid enough attention at present. In order to maximize the network lifetime, a deployment algorithm (UDA) for underwater sensor networks in ocean environment is proposed. UDA can determine and select the best cluster shape, then partition the space into layers and clusters while maintaining full coverage and full connectivity. In addition, nodes closer to sinks are possible to bear a heavier data-relaying mission. UDA sets different node deployment densities at different layers in response to the potential relay discrepancy. The simulation results suggest UDA can choose the proper cluster shape to get the maximum underwater wireless sensor network lifetime approximately.

scholarly journals Hybrid Cross Layer Mechanism For High Reliability In Under Water Wireless Sensor Network

2019 ◽  
Vol 9 (1) ◽  
pp. 1372-1376
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
High Reliability ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Delivery Ratio ◽  
Data Delivery ◽  
Underwater Sensor Networks ◽  
Water Sensor ◽  
Hybrid Cross

Underwater sensor network finds lot of applications in sea environment monitoring. Tsunami like conditions can be monitored and reported earlier so that people on shores can be safe. Due to nature of medium, the data delivery ratio in under water sensor networks is very low. The various problems in the underwater sensor networks are crucial delay, Double side spreading, multipath induced fading, bandwidth limitation, Doppler effects. These problems reduce the data delivery ratio, network lifetime and other parameters.In order to increase the performance of the underwater communication system,Reed Solomon encoding technique with hybrid cross layer methodis used in physical, data link and routing layer . The proposed method increase the reliability of underwater wireless sensor networks.

scholarly journals Spark-Based Parallel Genetic Algorithm for Simulating a Solution of Optimal Deployment of an Underwater Sensor Network

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2717 ◽  
Author(s):  
Peng Liu ◽  
Shuai Ye ◽  
Can Wang ◽  
Zongwei Zhu
Keyword(s):  
Genetic Algorithm ◽  
Sensor Network ◽  
Large Scale ◽  
Working Environment ◽  
Underwater Sensor Networks ◽  
Single Node ◽  
Running Time ◽  
Node Deployment ◽  
Underwater Sensor Network ◽  
Optimal Deployment

Underwater sensor networks have wide application prospects, but the large-scale sensing node deployment is severely hindered by problems like energy constraints, long delays, local disconnections, and heavy energy consumption. These problems can be solved effectively by optimizing sensing node deployment with a genetic algorithm. However, the genetic algorithm (GA) needs many iterations in solving the best location of underwater sensor deployment, which results in long running time delays and limited practical application when dealing with large-scale data. The classical parallel framework Hadoop can improve the GA running efficiency to some extent while the state-of-the-art parallel framework Spark can release much more parallel potential of GA by realizing parallel crossover, mutation, and other operations on each computing node. Giving full allowance for the working environment of the underwater sensor network and the characteristics of sensors, this paper proposes a Spark-based parallel GA to calculate the extremum of the Shubert multi-peak function, through which the optimal deployment of the underwater sensor network can be obtained. Experimental results show that while faced with a large-scale underwater sensor network, compared with single node and Hadoop framework, the Spark-based implementation not only significantly reduces the running time but also effectively avoids the problem of premature convergence because of its powerful randomness.

A Review of Recent Issues and Challenges of Fault Management Techniques in Underwater Wireless Sensor Network

2021 ◽  
pp. 101-119
Author(s):  
Nonita Sharma ◽  
Krishna Pal Sharma ◽  
Rajneesh Rani
Keyword(s):  
Sensor Networks ◽  
Data Gathering ◽  
Fault Management ◽  
Wireless Sensor ◽  
Underwater Sensor Networks ◽  
Media Access ◽  
Pros And Cons ◽  
Management Techniques ◽  
New Research ◽  
3D Topology

Underwater wireless sensor networks (UWSNs) are deployed to conduct cooperative surveillance and data gathering tasks in an acoustic region. Different nodes and ground-based stations use these networks interactively. UWSNs are currently facing problems and difficulties related to restricted bandwidth, substantial delay in propagation, 3D topology, control of media access, routing, use of resources, fault management, and energy limitations. The research community has given various methodologies over the past few decades to address these problems and challenges; however, owing to varying attributes of the underwater environment, some of them are still open to research. In this chapter, a survey of fault management techniques in UWSN regarding types of faults and their classification, environmental factors influencing the identification of faults, fault detection schemes, issues, and future directions is performed. This chapter outlines available fault management techniques and their pros and cons for further advancement in underwater sensor networks to highlight new research trends.

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