scholarly journals Distance Mapping Algorithm for Sensor Node Localization in WSNs

2019 ◽  
Vol 27 (2) ◽  
pp. 261-270
Author(s):  
Rong Tan ◽  
Yudong Li ◽  
Yifan Shao ◽  
Wen Si
Keyword(s):  
Sensor Node ◽  
Node Localization ◽  
Mapping Algorithm ◽  
Distance Mapping

scholarly journals Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

2021 ◽  
Author(s):  
Lismer Andres Caceres Najarro ◽  
Iickho Song ◽  
Kiseon Kim
Keyword(s):  
Sensor Node ◽  
State Of The Art ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Healthcare Industry ◽  
Target Node ◽  
Node Localization ◽  
Localization Accuracy ◽  
Fundamental Limitations ◽  
Points Of View

<p> </p><p>With the advances in new technological trends and the reduction in prices of sensor nodes, wireless sensor networks</p> <p>(WSNs) and their applications are proliferating in several areas of our society such as healthcare, industry, farming, and housing. Accordingly, in recent years attention on localization has increased significantly since it is one of the main facets in any WSN. In a nutshell, localization is the process in which the position of any sensor node is retrieved by exploiting measurements from and between sensor nodes. Several techniques of localization have been proposed in the literature with different localization accuracy, complexity, and hence different applicability. The localization accuracy is limited by fundamental limitations, theoretical and practical, that restrict the localization accuracy regardless of the technique employed in the localization process. In this paper, we pay special attention to such fundamental limitations from the theoretical and practical points of view and provide a comprehensive review of the state-of-the-art solutions that deal with such limitations. Additionally, discussion on the theoretical and practical limitations together with their recent solutions, remaining challenges, and perspectives are presented.</p> <p><br></p>

Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

2019 ◽  
pp. 1-14
Author(s):  
Alonshia S. Elayaraja
Keyword(s):  
Target Tracking ◽  
Sensor Node ◽  
Management Strategies ◽  
Extended Period ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensor Management ◽  
Node Localization ◽  
Time Optimal ◽  
Energy Consumption Rate

Many applications in wireless sensor networks perform localization of nodes over an extended period of time. Optimal selection algorithm poses new challenges to the overall transmission power levels for target detection, and thus, localized energy optimized sensor management strategies are necessary for improving the accuracy of target tracking. In this chapter, a proposal plan to develop a Bayesian localized energy optimized sensor distribution scheme for efficient target tracking in wireless sensor network is designed. The sensor node localization is done with Bayesian average, which estimates the sensor node's energy optimality. Then the sensor nodes are localized and distributed based on the Bayesian energy estimate for efficient target tracking. The sensor node distributional strategy improves the accuracy of identifying the targets to be tracked quickly. The performance is evaluated with parameters such as accuracy of target tracking, energy consumption rate, localized node density, and time for target tracking.

scholarly journals Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 343 ◽  
Author(s):  
Dezhi Han ◽  
Yunping Yu ◽  
Kuan-Ching Li ◽  
Rodrigo Fernandes de Mello
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Random Mutation ◽  
Localization Accuracy ◽  
De Algorithm ◽  
Distance Vector

The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.

RSS-Based Outdoor Localization with Wireless Sensor Networks in Practice

2015 ◽  
pp. 225-256 ◽  
Author(s):  
Tsenka Stoyanova ◽  
Fotis Kerasiotis ◽  
George Papadopoulos
Keyword(s):  
Sensor Node ◽  
Signal Propagation ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Node Localization ◽  
Internal Factors ◽  
Localization Accuracy ◽  
Factors Influencing ◽  
Outdoor Localization ◽  
Rf Signal

In this chapter the authors discuss the feasibility of sensor node localization by exploiting the inherent resources of WSN technology, such as the received signal strength (RSS) of the exchanged messages. The authors also present a brief overview of various factors influencing the RSS, including the RF-signal propagation and other topology parameters which influence the localization process and accuracy. Moreover, the RSS variability due to internal factors, related to the hardware implementation of a sensor node, is investigated in order to be considered in simulations of RSS-based outdoor localization scenarios. Localization considerations referring to techniques, topology parameters and factors influencing the localization accuracy are combined in simulation examples to evaluate their significance concerning target positioning performance. Finally, the RF propagation model and the topology parameters being identified are validated in real outdoor localization scenario.

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