Abstract
Self-organization and localization capabilities are among the most important requirements in wireless sensor networks (WSNs). While existing localization approaches mainly focus on enhancing the accuracy and minimizing the position error, particular attention has recently been given to reducing the localization algorithm implementation cost. This work re-explores the theory of wireless sensor network localization problem (SNLP), which is then re-considered as a multi-objective optimization problem (MOO-SNLP), maximizing the localization accuracy while minimizing the localization cost. The paper discusses a set of evaluation criteria and performance metrics in order to highlight the trade-off between location accuracy and implementation cost such as the energy consumption, communication overhead.