Iterative Localization in Decentralized Environment of WSN and IoT

In the recent literature, sensor localization has been considered as the most technical challenge of internet of thing and Wireless Sensor Networks. The main objective is to predict an accurate localization of sensor nodes. Recent approaches dealing with localization rely on meta-heuristics algorithms; hence, the localization procedure becomes an optimization issue in a multidimensional space. Bat algorithms are well suited for this kind of problems. It is also known in several recent papers that the Bat algorithm is well suited in space exploitation, but not as much in exploration. Throughout the paper, we propose an enhanced hybrid approach, namely “Enhanced Bat Algorithm with Doppler Effect or “EBADE”. Bat parameters are tuned using a modified frequency equation. EBADE computes thus iterative the position of the nodes through optimizing node Euclidean distances. Experimental results come up with remarkable improvement in terms of localization error and CPU run-time.

[1]  Pascal Lorenz,et al.  Moth Flame Optimization Algorithm Range-Based for Node Localization Challenge in Decentralized Wireless Sensor Network , 2019, Int. J. Distributed Syst. Technol..

[2]  Abderrahim Benslimane,et al.  Time-bounded localization algorithm based on distributed Multidimensional Scaling for Wireless Sensor Networks , 2014, 2014 IEEE International Conference on Communications (ICC).

[3]  Marko Beko,et al.  Elephant Herding Optimization Algorithm for Wireless Sensor Network Localization Problem , 2018, DoCEIS.

[4]  Aloor Gopakumar,et al.  Localization in wireless sensor networks using particle swarm optimization , 2008 .

[5]  Deepak Prashar,et al.  Performance Evaluation of the Optimized Error Correction Based Hop Localization Approach in a Wireless Sensor Network , 2019, Wireless Personal Communications.

[6]  Abdellatif Rahmoun,et al.  Intelligent Technique Based on Enhanced Metaheuristic for Optimization Problem in Internet of Things and Wireless Sensor Network , 2020, Int. J. Grid High Perform. Comput..

[7]  Fekher Khelifi,et al.  A new fuzzy logic based node localization mechanism for Wireless Sensor Networks , 2017, Future Gener. Comput. Syst..

[8]  Abdellatif Rahmoun,et al.  Whale Optimization Approach for Optimization Problem In Distributed Wireless Sensor Network , 2019, ICIST.

[9]  Ravindara Bhatt,et al.  Privacy Preservation in WSN for Healthcare Application , 2018 .

[10]  Pascal Lorenz,et al.  An effective Bat algorithm for node localization in distributed wireless sensor network , 2018, Secur. Priv..

[11]  Sonia Goyal,et al.  Flower pollination algorithm based localization of wireless sensor network , 2015, 2015 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS).

[12]  Ghulam Bhatti,et al.  Machine Learning Based Localization in Large-Scale Wireless Sensor Networks , 2018, Sensors.

[13]  Naser El-Sheimy,et al.  Localization of wireless sensor network using Bees Optimization Algorithm , 2010, The 10th IEEE International Symposium on Signal Processing and Information Technology.

[14]  Safa Hamdoun,et al.  RSSI-based Localization Algorithms using Spatial Diversity in Wireless Sensor Networks , 2014 .

[15]  Shiwen Mao,et al.  CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach , 2016, IEEE Transactions on Vehicular Technology.