Abstract
The field observation of a sensor node is signified by the location of the event occurrences. The various approaches to estimate the location of the sensor nodes (unknown node) approximate distances between sensor pairs by considering the known location of some of the sensor nodes (anchor nodes), like the DV-hop algorithm and its various successors. Here, the major challenge is to estimate precise distances between the node pairs using average hop sizes and the non-Euler shortest paths. This research gap motivates to propose an algorithm—RLO, a range-free localization using optimization in WSN. RLO defines the distance error factors with upper and lower bonds in a manner such that the unknown node of interest finds its optimum location. To obtain an optimum location, we apply linear programming and transformed the localization problem into the optimization problem. The validation of RLO by simulation experimentation shows that RLO is better to localize the unknown nodes by DV-hop and IDV algorithms by 6% and 3%, respectively, on average.
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Kumar, S., Batra, N., Kumar, S. (2022). Range-free Localization by Optimization in Anisotropic WSN. In: Dua, M., Jain, A.K., Yadav, A., Kumar, N., Siarry, P. (eds) Proceedings of the International Conference on Paradigms of Communication, Computing and Data Sciences. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-5747-4_14
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