An range-free localization scheme for large scale underwater wireless sensor networks

2009 ◽  
Vol 14 (5) ◽  
pp. 562-568 ◽  
Author(s):  
Yi Zhou ◽  
Bao-jun Gu ◽  
Kai Chen ◽  
Jian-bo Chen ◽  
Hai-bing Guan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Localization Scheme ◽  
Range Free

scholarly journals Hybrid Fuzzy Centroid with MDV-Hop BAT Localization Algorithms in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Chakchai So-In ◽  
Weerat Katekaew
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Effective ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Small Scale ◽  
Battery Life ◽  
Distance Information ◽  
Localization Scheme ◽  
Range Free

Many applications employing wireless sensor networks have been available in real-world scenarios. Their popularity is due to distinctive characteristics, for example, small scale, multisensing capability, and cost-effective deployment. However, there are constraints including routing, reliability, and especially localization, in particular without the aid of global positioning services, the lack of satellite coverage. In addition, if embedded, the overhead will be increased with hardware costs and shortened battery life. Thus, a range-free-based localization scheme is promising and is being pursued as a cost-effective approach. Centroid is one of the pioneer low complexity range-free estimation algorithms, and DV-Hop is another algorithm that has no requirements for distance information. However, their main drawbacks are location estimation precision. Recently, a soft-computing-based approach used to address uncertainty and approximation has been proposed as a low cost solution to gain precision, and, therefore, this research investigates its integration and then proposes a novel hybrid localization algorithm utilizing key characteristics of Centroid and DV-Hop. This hybrid scheme employs an extra weight with signal normalization derived from a fuzzy logic function in Centroid. The research also integrates a BAT algorithm of the modified DV-Hop. These combinations demonstrate the effectiveness in the simulation and location error reduction with time complexity trade-off.

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