ADAL: A distributed range-free localization algorithm based on a mobile beacon for wireless sensor networks

Author(s):  
E. Guerrero ◽  
H. G. Xiong ◽  
Q. Gao ◽  
G. Cova ◽  
R. Ricardo ◽  
...  
2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875627 ◽  
Author(s):  
Wenlan Wu ◽  
Xianbin Wen ◽  
Haixia Xu ◽  
Liming Yuan ◽  
Qingxia Meng

In this article, a novel range-free localization algorithm is proposed based on the modified expected hop progress for heterogeneous wireless sensor networks where all nodes’ communication ranges are different. First, we construct the new cumulative distribution function expression of expected hop progress to reduce the computational complexity. Then, the elliptical distance correction method is used to improve the accuracy of the estimation distance and simultaneously decrease overhead. Finally, using the modified distance, the coordinate of the unknown node can be obtained by maximum likelihood estimation. Compared with other algorithms for heterogeneous wireless sensor network, the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes.


2014 ◽  
Vol 9 (5) ◽  
Author(s):  
Xiaoming Wu ◽  
Hua Wu ◽  
Yang Liu ◽  
Jianping Xing ◽  
Mingyue Zhao

2013 ◽  
Vol 475-476 ◽  
pp. 564-568
Author(s):  
Wei Yong Jiang ◽  
Pin Wan ◽  
Yong Hua Wang ◽  
Dong Liang

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.


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