A GPS-Less Cell-Based Localization Technique for Wireless Sensor Networks

2012 ◽  
Vol 601 ◽  
pp. 376-382
Author(s):  
Xue Jun Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Level ◽  
Wireless Sensor ◽  
Transmission Power ◽  
Localization Algorithm ◽  
Localization Technique ◽  
Simulation Results

This paper presents a localization algorithm, namely Circle Based Localization (CBL) for GPS-less wireless sensor networks. CBL works by finding the centroid of intersection of any two circles. Furthermore, we study the effect of power level mismatch among anchors. Simulation results show that CBL can significantly improve the accuracy by 5% while reducing the transmission power of anchors.

scholarly journals Secure and Robust 3D Localization in Wireless Sensor Networks

2019 ◽  
Vol 9 (1S) ◽  
pp. 104-111
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Malicious Nodes ◽  
3D Localization ◽  
Secure Localization ◽  
Simulation Results ◽  
Two Phases

The fundamental capacity of a sensor system is to accumulate and forward data to the destination. It is crucial to consider the area of gathered data, which is utilized to sort information that can be procured using confinement strategy as a piece of Wireless Sensor Networks (WSNs).Localization is a champion among the most basic progressions since it agreed as an essential part in various applications, e.g., target tracking. If the client can't gain the definite area information, the related applications can't be skillful. The crucial idea in most localization procedures is that some deployed nodes with known positions (e.g., GPS-equipped nodes) transmit signals with their coordinates so as to support other nodes to localize themselves. This paper mainly focuses on the algorithm that has been proposed to securely and robustly decide thelocation of a sensor node. The algorithm works in two phases namely Secure localization phase and Robust Localization phase. By "secure", we imply that malicious nodes should not effectively affect the accuracy of the localized nodes. By “robust”, we indicate that the algorithm works in a 3D environment even in the presence of malicious beacon nodes. The existing methodologies were proposed based on 2D localization; however in this work in addition to security and robustness, exact localization can be determined for 3D areas by utilizing anefficient localization algorithm. Simulation results exhibit that when compared to other existing algorithms, our proposed work performs better in terms of localization error and accuracy.

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

Localization in Wireless Sensor Networks in Beacon Drifting Scenarios

2012 ◽  
Vol 562-564 ◽  
pp. 1234-1239
Author(s):  
Ming Xia ◽  
Qing Zhang Chen ◽  
Yan Jin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Probability Density ◽  
Sensor Nodes ◽  
Density Model ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Scenarios Simulation ◽  
Simulation Results

The beacon drifting problem occurs when the beacon nodes move accidentally after deployment. In this occasion, the localization results of sensor nodes in the network will be greatly affected and become inaccurate. In this paper, we present a localization algorithm in wireless sensor networks in beacon drifting scenarios. The algorithm first uses a probability density model to calculate the location reliability of each node, and in localization it will dynamically choose nodes with highest location reliabilities as beacon nodes to improve localization accuracy in beacon drifting scenarios. Simulation results show that the proposed algorithm achieves its design goals.

Correlation between Estimation Error and Possible Region in Localization Algorithms

2012 ◽  
Vol 457-458 ◽  
pp. 1514-1520
Author(s):  
Shi Hao Yan ◽  
Jian Ping Xing ◽  
De Qiang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Estimation Error ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Estimation Errors ◽  
Localization Algorithms ◽  
Localization Precision ◽  
Simulation Results ◽  
Definite Correlation

Many localization algorithms in wireless sensor networks mention possible regions to increase the degree of localization precision. In this paper, we present the definite correlation between the estimation error and the possible region. The estimation error, which is the most important indictor to judge the performance of a localization algorithm, is proportional to the square root of the area of the possible region and the factor of proportionality relates to the shape of the possible region. We also propose two applications of the definite correlation, including estimation errors detection and energy conservation. The simulation results show that the definite correlation is suitable for all kinds of possible regions and it is feasible to detect estimation errors and conserve energy when we fix reasonable areas of possible regions in wireless sensor networks.

scholarly journals Multihopping Multilevel Clustering Heterogeneity-Sensitive Optimized Routing Protocol for Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Muhammad Aslam ◽  
Fan Wang ◽  
Xiaopeng Hu ◽  
Muhammad Asad ◽  
Ehsan Ullah Munir
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Level ◽  
Cluster Formation ◽  
Base Station ◽  
Link Quality ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Transmission Power ◽  
Packet Drop

Effective utilization of energy resources in Wireless Sensor Networks (WSNs) has become challenging under uncertain distributed cluster-formation and single-hop intercluster communication capabilities. So, sensor nodes are forced to operate at expensive full rate transmission power level continuously during whole network operation. These challenging network environments experience unwanted phenomena of drastic energy consumption and packet drop. In this paper, we propose an adaptive immune Multihopping Multilevel Clustering (MHMLC) protocol that executes a Hybrid Clustering Algorithm (HCA) to perform optimal centralized selection of Cluster-Heads (CHs) within radius of centrally located Base Station (BS) and distributed CHs selection in the rest of network area. HCA of MHMLC also produces optimal intermediate CHs for intercluster multihop communications that develop heterogeneity-aware economical links. This hybrid cluster-formation facilitates the sensors to function at short range transmission power level that enhances link quality and avoids packet drop. The simulation environments produce fair comparison among proposed MHMLC and existing state-of-the-art routing protocols. Experimental results give significant evidence of better performance of the proposed model in terms of network lifetime, stability period, and data delivery ratio.

scholarly journals A Time Difference of Arrival-based Localization Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 80 ◽  
Author(s):  
Songbo Ji
Keyword(s):  
Wireless Sensor Networks ◽  
Electromagnetic Wave ◽  
Sensor Networks ◽  
Large Scale ◽  
Time Difference ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Simulation Results

<p class="Abstract"><span lang="EN-US">Aimed at solving the problem of local divergence and low data accuracy, this paper introduces a new Time Difference of Arrival(TDOA)-based localization algorithm (TBL) for the large-scale, high-density wireless sensor networks which are designed for real-time surveillance and unexpected incidents management. In particular, several means to improve the accuracy of distance measurement are investigated, and the TDOA method, based on the sound wave and electromagnetic wave to locate in the large-scale WSN, is discussed. Also, the well-designed circular location process has the advantage of better positioning accuracy and coverage percentage. Simulation results have confirmed the effectiveness of the formed TBL algorithm.</span></p>

Research on Wireless Sensor Networks with an Improved DV-Hop Localization Algorithm Based on Weighted Processing and Error Modification

2014 ◽  
Vol 1022 ◽  
pp. 396-401
Author(s):  
Hang Xia Zhou ◽  
Chen Cui ◽  
Jia Jun Ye
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Theoretical Analysis ◽  
Network Topology ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Nodes ◽  
Simulation Results

Regarding the conventional DV-Hop algorithm easily caused big error in a network topology scenario, this paper proposes an improved DV-Hop localization algorithm comprehensive consideration of all anchor nodes average one-hop distance and normalized weighted, use anchor nodes as unknown nodes calculating error and use the error optimizing accuracy. Theoretical analysis and simulation results show that the proposed algorithm has better locating performance in locating precision and precision stability.

Localization Algorithm Based on DV-HOP for Wireless Sensor Network

2011 ◽  
Vol 128-129 ◽  
pp. 909-913
Author(s):  
Yu Hu ◽  
Xue Mei Li
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Weighted Average ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Improved Algorithm

An improved DV-HOP localization algorithm is proposed in the paper, aiming at the traditional DV-HOP localization algorithm. The improved algorithm introduces threshold M, it uses the weighted average hop distances of anchor nodes within M hops to calculate the average hop distance of unknown nodes. In addition, the positioning results are corrected in the improved algorithm. The simulation results show that the improved localization algorithm effectively improves the positioning accuracy compared with the traditional DV-HOP localization algorithm, it is an effective localization algorithm for the wireless sensor networks.

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