Design of a Guideline for Range-based Localization Algorithms Evaluation Using Multiple Linear Regressions

Localization is an essential feature in numerous Wireless Sensor Network (WSN) applications, including tracking, health monitoring, and military supervision. Analytical modeling and analysis of the localization system remain challenging and infeasible since it offers oversimplified results with limited reliability to the evaluated cases. Likewise, disseminating test-beds involves a lot of effort, making the simulation phase indispensable to study the WSN localization. The defined localization model needs to ensure solid and pragmatic network assumptions during the simulation. However, most network simulators don't meet specific criteria related to network definition, such as scalability and heterogeneity. As part of this endeavor, a guideline for evaluating and analyzing technical methods of range-based localization is developed. Multiple linear regression is used to generate the different localization instances, which enables to support different and non-dependent parameters. The developed guideline for range-based localization is tested and validated for existing localization solutions.