scholarly journals Localization Algorithm Based on Iterative Centroid Estimation for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Jiang ◽  
Xin Wang ◽  
Li Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Centroid Estimation ◽  
Anchor Nodes ◽  
Localization Precision ◽  
Unknown Node ◽  
Received Signal Strength Indication

According to the application of range-free localization technology for wireless sensor networks (WSNs), an improved localization algorithm based on iterative centroid estimation is proposed in this paper. With this methodology, the centroid coordinate of the space enclosed by connected anchor nodes and the received signal strength indication (RSSI) between the unknown node and the centroid are calculated. Then, the centroid is used as a virtual anchor node. It is proven that there is at least one connected anchor node whose distance from the unknown node must be farther than the virtual anchor node. Hence, in order to reduce the space enclosed by connected anchor nodes and improve the location precision, the anchor node with the weakest RSSI is replaced by this virtual anchor node. By applying this procedure repeatedly, the localization algorithm can achieve a good accuracy. Observing from the simulation results, the proposed algorithm has strong robustness and can achieve an ideal performance of localization precision and coverage.

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.

PACMLA: A Localization Algorithm Based on Permutation and Combination Midnormal for Wireless Sensor Networks

2013 ◽  
Vol 475-476 ◽  
pp. 564-568
Author(s):  
Wei Yong Jiang ◽  
Pin Wan ◽  
Yong Hua Wang ◽  
Dong Liang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Cost ◽  
Wireless Sensor ◽  
Data Sets ◽  
Localization Algorithm ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Number Of Iterations ◽  
Range Free

Localization of sensors is one key technique in wireless sensor networks (WSN).Because the midnormal-based localization algorithm (MBLA) has shortcomings such as low accuracy, relatively large number of iterations, a localization algorithm based on permutation and combination midnormal (PACMLA) for WSN is proposed. Nodes are divided into anchor nodes and unknown nodes. In its own communication range, unknown node can communicate with anchor nodes. In PACMLA algorithm, the unknown node communicates with the anchor nodes in turn, and collects their coordinate information and RSSI value. Then by comparing the RSSI values received by unknown node, these RSSI values are formed an array in accordance with the order from small to large. Then starting from the first value of the RSSI array, each of these values and the value behind them will be combined into data sets. Finally, according to corresponding coordinate information of the RSSI value in the data sets, we will determine the position of the unknown node by Point In Which Side (PIWS) determination. In addition, our algorithm is a kind of Range-free algorithm, and it can cuts down the node energy cost. The experiment results illustrate that the PACMLA algorithm has lower error and higher accuracy.

One Anchor Distance and Angle Based Multi - Hop Adaptive Iterative Localization Algorithm for Wireless Sensor Networks

2010 ◽  
Vol 2 (3) ◽  
pp. 31-43 ◽  
Author(s):  
S. B. Kotwal ◽  
Shekhar Verma ◽  
G. S. Tomar ◽  
R. K. Abrol ◽  
Suryansh Nigam
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Error Propagation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Communication Range ◽  
Uncertainty Region ◽  
Angle Measurements ◽  
Anchor Nodes

This paper presents distance and angle measurements based Multi-Hop Adaptive and Iterative Localization algorithm for localization of unknown nodes in wireless sensor networks (WSNs). The present work determines uncertainty region of unknown nodes with respect to known (anchor) nodes using noisy distance and angle measurements. This node transmits its uncertainty region to other unknown nodes to help them determine their uncertainty region. Because of noisy distance and angle measurements, the error propagation increases the size of regions of nodes in subsequent hops. Using only one anchor node as reference, the proposed iterative localization algorithm reduces the error propagation of this noisy distance and angle measurements and the uncertainty region of all unknown nodes within a given communication range. The results clearly indicate the improved efficiency of the proposed algorithm in comparison with existing algorithms.

Study of Location Algorithm for Wireless Sensor Networks Based on Newton Iteration

2013 ◽  
Vol 645 ◽  
pp. 285-289
Author(s):  
Ying Liu ◽  
Xu Zhang ◽  
Dan Liu ◽  
Zhi Qiang Han
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Nonlinear Equation ◽  
Numerical Solutions ◽  
Newton Iteration ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Newton Iterative Method ◽  
Anchor Nodes ◽  
Unknown Node

The TDOA localization algorithm for wireless sensor networks can help us measure the time differences of an unknown node to more anchor nodes, which establish nonlinear equation of the differential distance between unknown node and anchor node. Newton iteration is the crucial method for nonlinear equation numerical solutions, so using the Newton iterative method can better achieve nonlinear optimization in TDOA location. The simulation results indicate that the algorithm can meet the requirement of localization and possesses the preferable localization precision.

One Anchor Distance and Angle Based Multi - Hop Adaptive Iterative Localization Algorithm for Wireless Sensor Networks

2012 ◽  
pp. 255-266
Author(s):  
S. B. Kotwal ◽  
Shekhar Verma ◽  
G. S. Tomar ◽  
R. K. Abrol
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Error Propagation ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Communication Range ◽  
Uncertainty Region ◽  
Angle Measurements ◽  
Anchor Nodes

This paper presents distance and angle measurements based Multi-Hop Adaptive and Iterative Localization algorithm for localization of unknown nodes in wireless sensor networks (WSNs). The present work determines uncertainty region of unknown nodes with respect to known (anchor) nodes using noisy distance and angle measurements. This node transmits its uncertainty region to other unknown nodes to help them determine their uncertainty region. Because of noisy distance and angle measurements, the error propagation increases the size of regions of nodes in subsequent hops. Using only one anchor node as reference, the proposed iterative localization algorithm reduces the error propagation of this noisy distance and angle measurements and the uncertainty region of all unknown nodes within a given communication range. The results clearly indicate the improved efficiency of the proposed algorithm in comparison with existing algorithms.

scholarly journals An improved DV-Hop localization with minimum connected dominating set for mobile nodes in wireless sensor networks

2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875563 ◽  
Author(s):  
Gulshan Kumar ◽  
Mritunjay Kumar Rai ◽  
Rahul Saha ◽  
Hye-jin Kim
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dominating Set ◽  
Connected Dominating Set ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Localization Algorithm ◽  
Mobile Nodes ◽  
Minimum Connected Dominating Set ◽  
Anchor Nodes

Localization is one of the key concepts in wireless sensor networks. Different techniques and measures to calculate the location of unknown nodes were introduced in recent past. But the issue of nodes’ mobility requires more attention. The algorithms introduced earlier to support mobility lack the utilization of the anchor nodes’ privileges. Therefore, in this article, an improved DV-Hop localization algorithm is introduced that supports the mobility of anchor nodes as well as unknown nodes. Coordination of anchor nodes creates a minimum connected dominating set that works as a backbone in the proposed algorithm. The focus of the research paper is to locate unknown nodes with the help of anchor nodes by utilizing the network resources efficiently. The simulated results in network simulator-2 and the statistical analysis of the data provide a clear impression that our novel algorithm improves the error rate and the time consumption.

scholarly journals A Combined Localization Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
State Of The Art ◽  
Sensor Nodes ◽  
Vehicle Tracking ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Environment And Health ◽  
Anchor Nodes ◽  
Positioning Algorithm

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.

scholarly journals Research on Algorithm of Three-Dimensional Wireless Sensor Networks Node Localization

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiang Minlan ◽  
Luo Jingyuan ◽  
Zou Xiaokang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Minimum Problem ◽  
Localization Algorithm ◽  
Node Localization ◽  
Anchor Nodes

This paper proposes a three-dimensional wireless sensor networks node localization algorithm based on multidimensional scaling anchor nodes, which is used to realize the absolute positioning of unknown nodes by using the distance between the anchor nodes and the nodes. The core of the proposed localization algorithm is a kind of repeated optimization method based on anchor nodes which is derived from STRESS formula. The algorithm employs the Tunneling Method to solve the local minimum problem in repeated optimization, which improves the accuracy of the optimization results. The simulation results validate the effectiveness of the algorithm. Random distribution of three-dimensional wireless sensor network nodes can be accurately positioned. The results satisfy the high precision and stability requirements in three-dimensional space node location.

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