APOTSA: Anchor placement optimisation using discrete Tabu search algorithm for area-based localisation

Recently, there has been an increasing interest in indoor localisation due to the demand for location-based services. Diverse techniques have been described in the literature to improve indoor localisation services, but their accuracy is significantly affected by the number and location of the anchors, which act as a reference point for localising tags in a given space. The authors focus on indoor area-based localisation. A set of anchors defines certain geographical areas, called residence areas, and the location of a tag is approximated by the residence area in which the tag is placed. Hence the position is not given by exact coordinates. In this approach, placing the anchors such that the resulting residence areas are small on average yields a high-quality localisation accuracy. The authors’ main contribution is the introduction of a discretisation method to calculate the residence areas for a given anchor placement more efficiently. This method reduces the runtime compared to the algorithms from the literature dramatically and hence allows us to search the solution space more efficiently. The authors propose APOTSA, a novel approach for discovering a high-quality placement of anchors to improve the accuracy of area-based indoor localisation systems while requiring a shorter execution time than existing approaches. The proposed algorithm is based on Tabu search and optimises the localisation accuracy by minimising the expected residence area. APOTSA's localisation accuracy and time of execution are evaluated by different indoor-localisation scenarios involving up to five anchors. The results indicate that the expected residence area and the time of execution can be reduced by up to 9.5% and 99% compared to the state-of-the-art local search anchors placement (LSAP) algorithm, respectively.