Localisation has become a major attraction of research in recent years in the field of wireless sensor networks (WSNs). It is required for various applications like monitoring of objects placed in indoors and outdoors...
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Localisation has become a major attraction of research in recent years in the field of wireless sensor networks (WSNs). It is required for various applications like monitoring of objects placed in indoors and outdoors environments. The main requirement in localisation is to assign a location to each node, since multiple sensor nodes in WSN are used to retrieve information. The aim of this research is to address a WSN localisation problem using various optimisation techniques. The concept of single anchor node placement at the centre of sensing field with its projection using hexagonal pattern is introduced. In this study, a novel hybrid optimisation technique named as dragonfly-firefly algorithm (DA-FA) is proposed. DA is an optimisation algorithm recently suggested based on the dragonfly's static and dynamic swarming behaviour. The suggested hybrid technique combines the exploration capability of explore DA and fireflyalgorithm's to exploit to obtain ideal global solutions. To check the effectiveness of DA-FA CEC 2019 benchmark functions are used for comparison with competitive algorithms. DA-FA converges fast and provide optimum solution for most of the benchmark functions. In addition, DA-FA outperforms well in terms of localisation error in comparison to existing localisation solutions.
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