scholarly journals Regional Optimization Dynamic Algorithm for Node Placement in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4216
Author(s):  
Yijie Zhang ◽  
Mandan Liu
Keyword(s):  
Sensor Nodes ◽  
Wireless Sensor ◽  
Search Performance ◽  
Search Range ◽  
Node Number ◽  
Dynamic Algorithm ◽  
Node Placement ◽  
Placement Optimization ◽  
Coverage Hole ◽  
Comparison Algorithms

Node placement is one of the basic problems in a Wireless Sensor Network (WSN). During the operation of a WSN, sensor nodes may fail or die suddenly, which may lead to a coverage hole. To solve this problem, the node placement needs to be re-optimized. The dimensions of node placement optimization are high because of the large node number. In view of this defect, a regional optimization dynamic algorithm is put forward. In this paper, the regional optimization problem of node placement is modeled, and a regional optimization dynamic algorithm with a mixed strategy for node placement (MRDA) is proposed. Simulation experiments are carried out for the proposed algorithm and other comparison algorithms. Results of experiments show that the proposed algorithm can greatly reduce the dimensions and narrow the search range, with a significant improvement in the search performance and convergence speed.

scholarly journals A Robust Method to Detect Coverage Holes And Network Re-Establishment for NB-IOT Enabled

2019 ◽  
Vol 8 (2S5) ◽  
pp. 137-143
Keyword(s):  
Maximum Error ◽  
Error Rates ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
High Coverage ◽  
Sensing Coverage ◽  
Prime Concern ◽  
Coverage Hole ◽  
Store And Forward ◽  
Coverage Holes

Sensing coverage with respect to WSN (Wireless Sensor Network) research has gained immense consideration. Implementation of WSNs in the domain of IoT (Internet of Things) ensures consideration of IoT features when thinking of sensing coverage. Both IoT and WSN are with respect to coverage hole metrics that includes network re-establishment, link establishing, throughput etc. Implementing sensor nodes may result in the issue of coverage holes if there is improper deployment of nodes. A coverage hole can exist in any region that is being monitored at any instance due to various purposes. As a result detecting coverage hole stand as a prime concern for gaining absolute coverage. Detecting coverage hole pose a big question for gaining high coverage in the Wireless Sensor Networks. The problem of coverage and connectivity particularly in coverage deployment strategy is analyzed for the weaker nodes and in case network design fails. The proposed algorithm referred to as ‘Store and Forward technique' aids in identifying the coverage holes and network re-establishing in WSNs and IoT. Hence with the help of Store and Forward technique, network re-establishing and network stability can be performed in case of a coverage hole issue. The proposed technique is mostly employed in networks having irregular connectivity, specifically within environments where mobility is high. It’s also beneficial in conditions with long transmission and variable delays, maximum error rates, or cases where there is no direct, end-to-end link. The experiment output represents that the proposed healing method magnifies coverage rate with only a few additional sensors in contrast to the related methods.

Improving the Mechanism of Detecting and Measuring Holes in Ad hoc Wireless Sensor Network

2019 ◽  
Author(s):  
Mohamed A Bayoumi ◽  
Tarek M Salem ◽  
Samir M Koriem
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Ad Hoc ◽  
Average Energy ◽  
Detection Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Small Individual ◽  
Coverage Hole ◽  
Hole Detection

Abstract Area detection and measuring is one of the most important problems in wireless sensor network because it mainly relates to the continuity and functionality of most routing protocols applied to the region of interest (ROI). Electronics failure, random deployment of nodes, software errors or some phenomena such as fire spreading or water flood could lead to wide death of sensor nodes. The damage on ROI can be controlled by detecting and calculating the area of the holes, resulting from the damaged sensor networks. In this paper, a new mathematical algorithm, wireless sensor hole detection algorithm (WHD), is developed to detect and calculate the holes area in ROI where the sensor nodes are spread randomly. WHD is developed for achieving quality of service in terms of power consumption and average hole detection time. The dynamic behavior of the proposed WHD depends on executing the following steps. Firstly, WHD algorithm divides down the ROI into many cells using the advantage of the grid construction to physically partition the ROI into many small individual cells. Secondly, WHD algorithm works on each cell individually by allocating the nearest three sensor nodes to each of the cell’s coordinates by comparing their positions, WHD connects each cell’s coordinate points with the selected sensor nodes by lines that construct a group of triangles, then WHD calculates the area of upcoming triangles. Repeating the previous step on all the cells, WHD can calculate and locate each hole in the ROI. The performance evaluation depends on the NS-2 simulator as a simulation technique to study and analyze the performance of WHD algorithm. Results show that WHD outperforms, in terms of average energy consumption and average hole discovery time, path density algorithm, novel coverage hole discovery algorithm and distriputed coverage hole Detection.

scholarly journals FLOWER POLLINATION AND GENETIC ALGORITHM BASED OPTIMIZATION FOR NODE DEPLOYMENT IN WIRELESS SENSOR NETWORKS

2020 ◽  
Vol 5 (2) ◽  
pp. 281-293
Author(s):  
Kapil Keswani ◽  
Dr. Anand Bhaskar
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Environment ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Field Energy ◽  
Main Concern ◽  
Node Placement ◽  
Flower Pollination

Wireless sensor network (WSN) most popular area of research where lots of work done in this field. Energy efficiency is one of the most focusing areas because life time of network is most common issue. In the WSN, the node placement is very essential part for the proper communication between the sensor nodes and base station (BS). For better communication nodes should be aware about their own or neighbor node’s location. Better optimization of resources and performance improvement are the main concern for the WSN. Optimal techniques should be utilized to place the nodes at the best possible locations for achieving the desired goal. For node placement, flower pollination optimization and genetic algorithm are useful to generate better result. BS is responsible for the communication of nodes with each other and it should be reachable to nodes. For this Region of Interest (RoI) is helpful to choose the best location. Placement of BS in the middle is suitable place for the static nodes deployment and there should be other strategy for the dynamic environment. Nodes should be connected to each other for the transmission of data from the source to BS properly. From the MATLAB simulation, it has been shown that the proposed methodology improves the network performance in terms of dead nodes, energy remaining and various packets sent to BS.

scholarly journals Energy Consumption Analysis in WSN Based on Node Placement Strategies

2018 ◽  
Vol 7 (3.12) ◽  
pp. 531
Author(s):  
R Shanmugavalli ◽  
P Subashini
Keyword(s):  
Energy Consumption ◽  
Power Distribution ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Finite Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Node Placement ◽  
Comparison Results

Wireless Sensor Networks (WSNs) is a collection of devices and sensor nodes connected with wireless network and communicate with one another via radio signals. Sensor in WSN is an autonomous (self-configuring) device used to sense the light, heat, motion, moisture and pressure etc that communicate with their neighbor nodes. Node placement is a technique that places the nodes effectively in the specified network environment. In WSN basically, wireless sensor network includes different topologies namely star, point-to-point, ring, bus, mesh and hybrid. In recent years, research has been carried out on different node placement strategies and produced different results based on its performance that includes power distribution and energy consumption of sensors. Energy consumption and network lifetime are considered to be the critical issues as the nodes are powered by the batteries which have finite energy reservoirs. In this paper, three different node placements namely Random, Uniform and Grid with respect to AODV (Ad hoc On-Demand Distance Vector) protocol is evaluated in order to analyze the energy factor during wireless communication. The performance metrics used to measure the analysis are Energy Consumption Average Jitter, Average End-to-End Delay, Average Throughput and Average Packet Delivery Ratio. The comparison results suggests that Grid node placement performs well in grid scenarios and shows best for specific performance metrics.  

scholarly journals Coverage Hole Recovery Algorithm Based on Molecule Model in Heterogeneous WSNs

2017 ◽  
Vol 12 (4) ◽  
pp. 562 ◽  
Author(s):  
Xiaoli Song ◽  
Yunzhan Gong ◽  
Dahai Jin ◽  
Qiangyi Li ◽  
Hengchang Jing
Keyword(s):  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Recovery Algorithm ◽  
Heterogeneous Sensor Networks ◽  
Coverage Hole ◽  
Sensing Model ◽  
Heterogeneous Nodes ◽  
Molecule Model

In diverse application fields, the increasing requisitions of Wireless Sensor Networks (WSNs) have more and more research dedicated to the question of sensor nodes’ deployment in recent years. For deployment of sensor nodes, some key points that should be taken into consideration are the coverage area to be monitored, energy consumed of nodes, connectivity, amount of deployed sensors and lifetime of the WSNs. This paper analyzes the wireless sensor network nodes deployment optimization problem. Wireless sensor nodes deployment determines the nodes’ capability and lifetime. For node deployment in heterogeneous sensor networks based on different probability sensing models of heterogeneous nodes, the author refers to the organic small molecule model and proposes a molecule sensing model of heterogeneous nodes in this paper. DSmT is an extension of the classical theory of evidence, which can combine with any type of trust function of an independent source, mainly concentrating on combined uncertainty, high conflict, and inaccurate source of evidence. Referring to the data fusion model, the changes in the network coverage ratio after using the new sensing model and data fusion algorithm are studied. According to the research results, the nodes deployment scheme of heterogeneous sensor networks based on the organic small molecule model is proposed in this paper. The simulation model is established by MATLAB software. The simulation results show that the effectiveness of the algorithm, the network coverage, and detection efficiency of nodes are improved, the lifetime of the network is prolonged, energy consumption and the number of deployment nodes are reduced, and the scope of perceiving is expanded. As a result, the coverage hole recovery algorithm can improve the detection performance of the network in the initial deployment phase and coverage hole recovery phase.

Node Placement Strategy in Wireless Sensor Network

2013 ◽  
Vol 5 (2) ◽  
pp. 18-31 ◽  
Author(s):  
Puteri Azwa Ahmad ◽  
M. Mahmuddin ◽  
Mohd Hasbullah Omar
Keyword(s):  
Sensor Networks ◽  
Region Of Interest ◽  
Target Position ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Node Placement ◽  
Random Deployment ◽  
Virtual Force ◽  
Coverage And Connectivity

The performance and quality of services in wireless sensor networks (WSNs) depend on coverage and connectivity. Node placement is a fundamental issue closely related to the coverage and connectivity in sensor networks. Node placement influences the target position, coverage area, and connectivity in sensor networks. In random deployment, sensor nodes are deployed randomly in a non-invasive way. The deployment process may cause issues like coverage holes, overlapping, and connectivity failure. Enhancing coverage and connectivity are important for sensor networks to provide a reliable communication within sensing. Placing many sensor nodes in a WSN application region area is not the best solution due to cost and it results in multiple sensors used. Mobile sensor node is used as an alternative to overcome the random deployment problem. The virtual force based self node deployment is used in the mobility sensor to improve the coverage and connectivity area. Virtual Force Algorithm (VFA) approach using virtual repulsive and attractive forces is used to find the optimal node placement to minimize the problems. Simulation results proofed that a uniform deployment achieved using VFA approach with an optimal sensing range to cover the region of interest.

scholarly journals Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 189
Author(s):  
Yijie Zhang ◽  
Mandan Liu
Keyword(s):  
Optimization Algorithm ◽  
Low Cost ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Placement Problem ◽  
Node Placement ◽  
Multi Objective ◽  
Placement Optimization ◽  
Monitoring Accuracy ◽  
Encoding Method

The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption and some other factors. In order to improve the convergence speed of a node placement optimization algorithm, the encoding method is improved in this paper. The degressive ary number encoding is further extended to a multi-objective optimization problem. Furthermore, the adaptive changing rule of ary number is proposed by analyzing the experimental results of the N-ary number encoded algorithm. Then a multi-objective optimization algorithm adopting the adaptive degressive ary number encoding method has been used in optimizing the node placement in WSN. The experiments show that the proposed adaptive degressive ary number encoded algorithm can improve both the optimization effect and search efficiency when solving the node placement problem.

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