A Novel Range Free Localization Algorithm in Wireless Sensor Networks Based on Connectivity and Genetic Algorithms

Noting the vital importance of localization using wireless sensor networks in real-world applications, many limitations of existing techniques urge us to seek more advanced localization algorithms. This paper presents a new range-free algorithm which takes advantages of genetic algorithms (GAs) to optimize multi-objective functions used in calculating an unknown position of normal node. The proposed algorithm, so far has improved the typical rage-free algorithms. It has good impact on the solving of localization problems with high accuracy. The first part illustrates typical based DV-hop localization algorithms. The principle of position estimation via genetic algorithms is introduced later. A proposed objective function to be optimized is defined in a next part, and its optimization based on GAs allows the unknown position’s computation. The new algorithm has been proved functional by theoretical analysis and simulation results. We have also proved the efficient performance of the proposed approach by comparing it to some state-of-the-art techniques.

[1]  Reza Akbari,et al.  A multilevel evolutionary algorithm for optimizing numerical functions , 2011 .

[2]  M. Begbie,et al.  Design and simulation of a multi-function MEMS sensor for health and usage monitoring , 2010, 2010 Prognostics and System Health Management Conference.

[3]  Hongdong Jia,et al.  A hybrid localization algorithm based on DV-Distance and the twice-weighted centroid for WSN , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[4]  Lotfi Nabli,et al.  FAULT DIAGNOSIS USING GENETIC ALGORITHMS AND PRINCIPAL CURVES , 2013 .

[5]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..

[6]  Kalyanmoy Deb,et al.  Messy Genetic Algorithms: Motivation, Analysis, and First Results , 1989, Complex Syst..

[7]  Lalit M. Patnaik,et al.  Adaptive probabilities of crossover and mutation in genetic algorithms , 1994, IEEE Trans. Syst. Man Cybern..

[8]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.

[9]  Euntai Kim,et al.  Robust DV-hop algorithm for localization in Wireless Sensor Network , 2010, ICCAS 2010.

[10]  Noureddine Liouane,et al.  A Selective 3-Anchor DV-Hop Algorithm Based On the Nearest Anchor for Wireless Sensor Network , 2014 .

[11]  Kam Tim Woo,et al.  GPS Localization Accuracy Improvement by Fusing Terrestrial TOA Measurements , 2010, 2010 IEEE International Conference on Communications.

[12]  Lijun Liu,et al.  An Adaptive Hybrid Localization Algorithm for Wireless Sensor Network , 2012, 2012 Second International Conference on Instrumentation, Measurement, Computer, Communication and Control.

[13]  Makhlouf Aliouat,et al.  Secure DV‐Hop localization scheme against wormhole attacks in wireless sensor networks , 2012, Trans. Emerg. Telecommun. Technol..

[14]  Shirshu Varma,et al.  Distance measurement and error estimation scheme for RSSI based localization in Wireless Sensor Networks , 2009, 2009 Fifth International Conference on Wireless Communication and Sensor Networks (WCSN).

[15]  Brian D. O. Anderson,et al.  Wireless sensor network localization techniques , 2007, Comput. Networks.

[16]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[17]  Lothar M. Schmitt,et al.  Theory of Genetic Algorithms II: models for genetic operators over the string-tensor representation of populations and convergence to global optima for arbitrary fitness function under scaling , 2004, Theor. Comput. Sci..

[18]  Winston Khoon Guan Seah,et al.  Localization in underwater sensor networks: survey and challenges , 2006, Underwater Networks.