LETTERS EXTRACTION IN SIGN BOARD USING VARIOUS OPTIMIZATION TECHNIQUES
Journal Title: Engineering and Technology Journal - Year 2017, Vol 2, Issue 2
Abstract
Accurate localization of randomly deployed sensor nodes is critically important in wireless sensor networks (WSNs) deployed for monitoring and tracking applications. The localization challenge has been posed as a multidimensional global optimization problem in earlier literature. Many swarm intelligence algorithms have been proposed for accurate localization. The untapped vast potential of the BFO algorithm has inspired the research presented in this paper. The ABC algorithm has been investigated as a tool for anchor-assisted sensor localization in WSNs. Results of Matlab simulation of BFO-based multistage localization has been presented. Further, the results are compared with those of the localization method based on the particle swarm optimization (PSO) algorithm. A comparison of the performances of BFO and PSO algorithms has been presented in terms of the number of nodes localized, localization accuracy and the computation time. The results show that the ABC algorithm delivers higher accuracy of localization than the PSO algorithm does; but, it takes longer to converge. This results in a tradeoff between speed and accuracy of localization in WSNs.
Authors and Affiliations
Nutan, Punit Kaushik
Keywords
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