scholarly journals A Voronoi Based Coverage Enhancement for Wireless Sensor Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 3845-3850
Keyword(s):  
Physical Distance ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Sensor Deployment ◽  
Sensor Coverage ◽  
Commercial Development ◽  
Coverage Area ◽  
The Cost ◽  
Coverage Holes ◽  
Modern Technologies

Wireless sensor network which competes with the modern technologies also paves the way for research and commercial development. Mobile and static sensors form a network that balances sensor coverage and the cost of the sensor. For this a thorough study of the coverage area and mobility of mobile sensor node is necessary. Coverage in wireless networks invoke the observation of physical distance enclosed by the sensors. Voronoi diagrams are used to find out the coverage holes and design movement – assisted sensor deployment protocols, VEC that works on the principle of moving sensors whereas Voronoi based works on the basis of load balancing. The algorithms gain sensor energy stabilization and small effect of deployment energy utilization. Its effectiveness is examined in terms of coverage, uniformity, time and distance. Key words - Sensor deployment,

scholarly journals Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation Errors

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7121
Author(s):  
Chiu-Han Hsiao ◽  
Frank Yeong-Sung Lin ◽  
Hao-Jyun Yang ◽  
Yennun Huang ◽  
Yu-Fang Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Daily Life ◽  
Pearson Correlation ◽  
Error Tolerance ◽  
Wireless Sensor ◽  
Sensor Deployment ◽  
Estimation Errors ◽  
The Cost ◽  
Distribution Problems

As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield results within the error tolerance. The correlation-aware method is also designed in a mathematical model that combines theoretical and practical perspectives. The sensor deployment strategies, including XGBoost, Pearson correlation, and Lagrangian Relaxation (LR), are determined to minimize deployment costs while maintaining estimation errors below a given threshold. Moreover, the results significantly ensure the accuracy of the gathered information while minimizing the cost of deployment and maximizing the lifetime of the WSN. Furthermore, the proposed solution can be readily applied to sensor distribution problems in various fields.

Wireless Sensor Node Placement Using Hybrid Genetic Programming and Genetic Algorithms

2012 ◽  
pp. 125-144
Author(s):  
Arpit Tripathi ◽  
Pulkit Gupta ◽  
Aditya Trivedi ◽  
Rahul Kala
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Genetic Programming ◽  
Ease Of Use ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimal Placement ◽  
Coverage Area ◽  
Node Placement

The ease of use and re-configuration in a wireless network has played a key role in their widespread growth. The node deployment problem deals with an optimal placement strategy of the wireless nodes. This paper models a wireless sensor network, consisting of a number of nodes, and a unique sink to which all the information is transmitted using the shortest connecting path. Traditionally the systems have used Genetic Algorithms for optimal placement of the nodes that usually fail to give results in problems employing large numbers of nodes or higher areas to be covered. This paper proposes a hybrid Genetic Programming (GP) and Genetic Algorithm (GA) for solving the problem. While the GP optimizes the deployment structure, the GA is used for actual node placement as per the GP optimized structure. The GA serves as a slave and GP serves as master in this hierarchical implementation. The algorithm optimizes total coverage area, energy utilization, lifetime of the network, and the number of nodes deployed. Experimental results show that the algorithm could place the sensor nodes in a variety of scenarios. The placement was found to be better than random placement strategy as well as the Genetic Algorithm placement strategy.

Analysis of Sensors’ Coverage through Application-Specific WSN Provisioning Tool

2012 ◽  
pp. 306-317
Author(s):  
Sami J. Habib
Keyword(s):  
Graphical User Interface ◽  
Search Space ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Coverage Ratio ◽  
Custom Made ◽  
X Cells ◽  
The Cost ◽  
The Relationship ◽  
Application Specific

This paper presents an automated provisioning tool for the deployment of sensors within wireless sensor networks (WSN) where we have employed evolutionary approach as a search technique to find the maximal coverage under minimal deployment cost. The coverage area is partitioned into M by N cells to reduce the search space from continuous to discrete by considering the placement of sensors at the centroid of each cell. The author has explored the relationship between various cell’s sizes versus the total number of deployed sensors. The experimental results show that when the number of cells to cover the service area from X by X cells to 2X by 2X cells is increased, on average this increases the cost by 3 folds. In this regard, it is due to the increase of the number of required sensors by an average of six folds, while improving the coverage ratio by only 9%. A custom-made graphical user interface (GUI) has been developed and embedded within the proposed automated provisioning tool to illustrate the deployment area with the placed sensors at step of the deployment process.

Analysis of Sensors’ Coverage through Application-Specific WSN Provisioning Tool

2011 ◽  
Vol 3 (1) ◽  
pp. 51-62
Author(s):  
Sami J. Habib
Keyword(s):  
Search Space ◽  
Wireless Sensor ◽  
Search Technique ◽  
Coverage Area ◽  
Coverage Ratio ◽  
Custom Made ◽  
X Cells ◽  
The Cost ◽  
The Relationship ◽  
Application Specific

This paper presents an automated provisioning tool for the deployment of sensors within wireless sensor networks (WSN) where we have employed evolutionary approach as a search technique to find the maximal coverage under minimal deployment cost. The coverage area is partitioned into M by N cells to reduce the search space from continuous to discrete by considering the placement of sensors at the centroid of each cell. The author has explored the relationship between various cell’s sizes versus the total number of deployed sensors. The experimental results show that when the number of cells to cover the service area from X by X cells to 2X by 2X cells is increased, on average this increases the cost by 3 folds. In this regard, it is due to the increase of the number of required sensors by an average of six folds, while improving the coverage ratio by only 9%. A custom-made graphical user interface (GUI) has been developed and embedded within the proposed automated provisioning tool to illustrate the deployment area with the placed sensors at step of the deployment process.

Wireless Sensor Node Placement Using Hybrid Genetic Programming and Genetic Algorithms

2011 ◽  
Vol 7 (2) ◽  
pp. 63-83 ◽  
Author(s):  
Arpit Tripathi ◽  
Pulkit Gupta ◽  
Aditya Trivedi ◽  
Rahul Kala
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Genetic Programming ◽  
Ease Of Use ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimal Placement ◽  
Coverage Area ◽  
Node Placement

The ease of use and re-configuration in a wireless network has played a key role in their widespread growth. The node deployment problem deals with an optimal placement strategy of the wireless nodes. This paper models a wireless sensor network, consisting of a number of nodes, and a unique sink to which all the information is transmitted using the shortest connecting path. Traditionally the systems have used Genetic Algorithms for optimal placement of the nodes that usually fail to give results in problems employing large numbers of nodes or higher areas to be covered. This paper proposes a hybrid Genetic Programming (GP) and Genetic Algorithm (GA) for solving the problem. While the GP optimizes the deployment structure, the GA is used for actual node placement as per the GP optimized structure. The GA serves as a slave and GP serves as master in this hierarchical implementation. The algorithm optimizes total coverage area, energy utilization, lifetime of the network, and the number of nodes deployed. Experimental results show that the algorithm could place the sensor nodes in a variety of scenarios. The placement was found to be better than random placement strategy as well as the Genetic Algorithm placement strategy.

Active and Trust Based Packet Transfer Method via Route Tracking for Wireless Sensor Networks

2019 ◽  
Vol 8 (6S2) ◽  
pp. 221-224
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Sensor Systems ◽  
Remote Sensor ◽  
Dynamic Source ◽  
Transfer Method ◽  
The Cost ◽  
Ebb And Flow ◽  
The Way

Trust is critical in remote sensor systems to exchange the information from source to goal. The Dynamic Source Protocol computes the substitute way, if any hub neglects to exchange the information. The Dynamic Source Protocol does not have any worked in usefulness to figure a substitute way if the way has a vindictive hub. With the cost of an interloper recognition framework we can identify the vindictive hub and modify the information/parcel exchange way. Notwithstanding, gatecrasher location framework is extremely costly for remote sensor systems and there is no certification in identifying a malevolent hub. In the ebb and flow look into a trust-based approach is prescribed to limit the overheads of gatecrasher location framework and it likewise recognizes the anomalous conduct hubs. The proposed demonstrate utilizes the rehashed recreations to distinguish flawed hubs through the agreeable exertion in the sensor organize and additionally judges the trust of progressive hubs. Reenactments were exhibited for standardized result of parcel dropping, normal rebate result, and trust connection.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

scholarly journals Estimation of Optimum Rendezvous Point for Mobile Sink (ORP-MS) in WSN

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1322 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav J Nigam
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
High Throughput ◽  
Mobile Sink ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Rendezvous Point ◽  
Coverage Holes

Clustering of the sensors in wireless sensor network is done to achieve energy efficiency. The nodes, which are unable to join any cluster, are referred to as isolated nodes and tend to transfer information straight to the base station. It is palpable that isolated nodes and cluster heads communicate with the base station and tend to exhaust their energy leaving behind coverage holes. In this paper, we propose the innovative clustering scheme using mobile sink approach to extend networks lifetime. The proposed (ORP-MS) algorithm is implemented in MATLAB 2017a and the results revealed that the proposed algorithm outdid the existing algorithms in terms networks lifetime and energy efficiency simultaneously achieved high throughput.  

Pattern Mutation in Wireless Sensor Deployment

2010 ◽  
Author(s):  
Xiaole Bai ◽  
Ziqiu Yun ◽  
Dong Xuan ◽  
Weijia Jia ◽  
Wei Zhao
Keyword(s):  
Wireless Sensor ◽  
Sensor Deployment
Sign in / Sign up

Export Citation Format

Share Document