HSA Based Sensor Nodes Deployment Strategy for Coverage and Connectivity in WSNs

2021 ◽  
pp. 73-81
Author(s):  
Subash Harizan ◽  
Pratyay Kuila ◽  
Rohit Kumar Das
Keyword(s):  
Sensor Nodes ◽  
Deployment Strategy ◽  
Coverage And Connectivity

Deployment Strategy in Distributed Underwater Sensor Networks

2014 ◽  
Vol 602-605 ◽  
pp. 3643-3647
Author(s):  
Li Yan Liu ◽  
Rong Fu ◽  
Yi He ◽  
Ying Qian Zhang
Keyword(s):  
Network Performance ◽  
Heuristic Method ◽  
Grid Method ◽  
Sensor Nodes ◽  
Triangular Grid ◽  
Underwater Sensor Networks ◽  
Network Coverage ◽  
Coverage Ratio ◽  
Initial Node ◽  
Deployment Strategy

Distributed underwater sensor network coverage is divided into two main categories: deterministic coverage and stochastic coverage. A strategy is put forward to deploy determinate area by using a triangular-grid method. When a coverage ratio is known, the distance between nodes can be adjusted to meet the coverage ratio in the monitored area, and the least number of sensor nodes can be calculated. Also a heuristic method is proposed for stochastic area deployment strategy. It is under the premise that the initial node location randomly deployed is given, using Voronoi diagram, the not easiest monitored path is searched, and the network coverage performance is improved by configuring the new nodes in the path. Finally it is proved that network performance is more improved by the simulation experiments, when one to four nodes are configured in the easiest breach path.

scholarly journals An Enhanced Underwater Linear Wireless Sensor Network Deployment Strategy for Data Collection

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Zahoor Ahmed ◽  
Kamalrulnizam Abu Bakar
Keyword(s):  
Wireless Sensor Network ◽  
Data Collection ◽  
Sensor Network ◽  
Research Work ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Deployment Strategy ◽  
Underwater Pipeline

The deployment of Linear Wireless Sensor Network (LWSN) in underwater environment has attracted several research studies in the underwater data collection research domain. One of the major issues in underwater data collection is the lack of robust structure in the deployment of sensor nodes. The challenge is more obvious when considering a linear pipeline that covers hundreds of kilometers. In most of the previous work, nodes are deployed not considering heterogeneity and capacity of the various sensor nodes. This lead to the problem of inefficient data delivery from the sensor nodes on the underwater pipeline to the sink node at the water surface. Therefore, in this study, an Enhanced Underwater Linear Wireless Sensor Network Deployment (EULWSND) has been proposed in order to improve the robustness in linear sensor underwater data collection. To this end, this paper presents a review of related literature in an underwater linear wireless sensor network. Further, a deployment strategy is discussed considering linearity of the underwater pipeline and heterogeneity of sensor nodes. Some research challenges and directions are identified for future research work. Furthermore, the proposed deployment strategy is implemented using AQUASIM and compared with an existing data collection scheme. The result demonstrates that the proposed EULWSND outperforms the existing Dynamic Address Routing Protocol for Pipeline Monitoring (DARP-PM) in terms of overhead and packet delivery ratio metrics. The scheme performs better in terms of lower overhead with 17.4% and higher packet delivery with 20.5%.

The Optimal Transmission Range for Strip-Based Wireless Sensor Networks

2011 ◽  
Vol 121-126 ◽  
pp. 4213-4217
Author(s):  
Zheng Jie Wang ◽  
Xiao Guang Zhao ◽  
Xu Qian ◽  
Xue Zhen Cheng
Keyword(s):  
Sensor Networks ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Effect ◽  
Energy Hole ◽  
Deployment Strategy ◽  
Transmission Distance ◽  
Multihop Communication ◽  
Energy Consumption Model

Strip-based sensor networks consist of a large amount of sensor nodes, which is characterized by multihop communication patterns. The nodes closer to the base station are required to forward more data than the nodes farther from the base station, leading to the problem of the energy hole and leaving the the areas of the network unmonitored. This paper analyzes energy consumption model of the uniform deployment and the nonuniform deployment and proves that there is an optimal transmission distance for these deployment strategies. The analysis shows clearly that the nonuniform deployment is more energy effect and more energy balance, which extend the network lifetime compared with the uniform deployment strategy.

scholarly journals A Novel Coverage Improved Deployment Strategy for Wireless Sensor Network

2021 ◽  
Author(s):  
Sathees Lingam Paulswamy ◽  
A.Andrew Roobert ◽  
K. Hariharan
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Surface Coverage ◽  
Region Of Interest ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cumulative Number ◽  
Deployment Strategy ◽  
New Strategy ◽  
Minimum Number

Abstract Coverage of the bounded region gets importance in Wireless Sensor Network (WSN). Area coverage is based on effective surface coverage with a minimum number of sensor nodes. Most of the researchers contemplate the coverage region of interest as a square and manifest the radio ranges as a circle. The area of a circle is much higher than the area of a square because of the perimeter. To utilize the advantage of the circle, the coverage region of interest is presumed as a circle for sensor node deployment. This paper proposes a novel coverage improved disc shape deployment strategy. Comparative analysis has been observed between circle and square regions of interest based on the cumulative number of sensor nodes required to cover the entire region. A new strategy named as disc shape deployment strategy is also proposed. Traditional hexagon and strip-based deployment strategies are compared with the disc shape deployment strategy. The simulation result shows that the circle shape coverage region of interest extremely reduces the required number of sensor nodes. The proposed deployment strategy provides desirable coverage, and it requires few more sensor nodes than hexagon shape deployment strategy.

A Uniformly Distributed Mobile Sensor Nodes Deployment Strategy Using Swarm Intelligence

2015 ◽  
pp. 537-572
Author(s):  
Chinmoy Ghorai ◽  
Arpita Debnath ◽  
Abhijit Das
Keyword(s):  
Swarm Intelligence ◽  
Sensor Nodes ◽  
Optimal Placement ◽  
Mobile Nodes ◽  
Distributed Sensor ◽  
Physical Conditions ◽  
Deployment Strategy ◽  
Movement Strategies ◽  
Mobile Sensor Nodes ◽  
The Universe

WSN consists of spatially dispersed and dedicated sensors for monitoring the physical conditions of the universe and organizing the collected data at a central location. WSN incorporates a gateway that provides wireless connectivity back to the wired world and distributed sensor nodes. Various applications have been proposed for WSN like Ecosystem and Seismic monitoring, where deployment of nodes in a suitable manner is of an immense concern. Currently, sensor nodes are mobile in nature and they are deployed at an accelerated pace. This chapter focuses on developing the mobile nodes in an apt technique to meet the needs of WSNs properly. It considers the swarm intelligence-based movement strategies with the assistance of local communications through which the randomly deployed sensors can arrange themselves to reach the optimal placement to meet the issues like lower cost, lower power consumption, simpler computation, and better sensing of the total area.

scholarly journals A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Fu Xiao ◽  
Yang Yang ◽  
Ruchuan Wang ◽  
Lijuan Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Computing Power ◽  
Deployment Strategy ◽  
Coverage Model ◽  
Minimum Number ◽  
Random Method

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes’ radius is deduced; also the minimum number of sensor nodes to maintain network area’s full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme.

scholarly journals Sensor Nodes Deployment Strategy for Monitoring Roadside Biomass Carbon Stocks of Tourism Destination: A Case of Wulong World Natural Heritage, China

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jun Liu ◽  
Xi Yang ◽  
Hao Long Liu ◽  
Zhi Qiao
Keyword(s):  
Land Use ◽  
Carbon Stocks ◽  
Tourism Industry ◽  
Sensor Nodes ◽  
Biomass Carbon ◽  
Natural Heritage ◽  
Deployment Strategy ◽  
Wide Range ◽  
Vegetation Carbon ◽  
World Natural Heritage

Since the late 1978s, China has experienced one of the highest tourism growth rates in the world, which in turn has driven extensive land-use and land-cover change. The aim of this research is to develop a sensor nodes positioning strategy for detecting land use related dynamics of vegetation carbon stocks of Wulong world natural heritage. Based on the assessment of road networks’ influences on biomass carbon stocks, roadside biomass carbon stocks risk index was proposed as a sensor deployment strategy to identify the optimal positions of the sensors to detect the changes in vegetation carbon stocks. Forest and cropland around the lower levels of roads should be the most important region of sensor nodes deployment strategy. The results generated from this study have the ability to achieve optimal solution of spatial positioning problem with minimum number of sensors in biomass carbon monitoring sensor networks. This analysis appears to have great potential for a wide range of practical applications in tourism industry in China.

scholarly journals Strip-based deployment with cooperative communication to achieve connectivity and information coverage in wireless sensor networks

2019 ◽  
Vol 15 (10) ◽  
pp. 155014771988488
Author(s):  
Wei Cheng ◽  
Xiaolin Lu ◽  
Yong Li ◽  
Hui Wang ◽  
Lei Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cooperative Communication ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
New Strategy ◽  
Optimal Deployment ◽  
Coverage And Connectivity ◽  
The Relationship ◽  
Information Coverage

Coverage and connectivity in wireless sensor network have been studied extensively in existing research works with physical and information coverage. The optimal deployment to achieve both information coverage and connectivity, on arbitrary values of the ratio of rc and rs, has been studied in previous work; meanwhile, the extended strip-based deployment based on information coverage is also studied. Either information coverage or cooperative communication could exploit collaboration of sensor nodes to improve the efficiency of deployment, while how good is strip-based deployment with both information coverage and cooperative communication is worth to be measured when the value of rc/ rs is varied. In this article, the relationship between the density of sensors needed to achieve physical or information coverage and connectivity and the variety of rc/ rs is derived in closed form for strip-based deployment of wireless sensor networks with cooperative communication. Then, a summary of different combinations of coverage and connectivity is provided, that physical or information coverage with or without cooperative communication could be employed to achieve full coverage and connectivity for strip-based deployment. Finally, some new strategy could be proposed based on the fusion of physical and information coverage to improve strip-based deployment. Some numerical results are provided to show the efficiency of all schemes to help researchers design more effective deployment schemes.

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