open-LQE is my PhD project which is done in collaboration between CISTER at ISEP/IPP (Instituto Superior de Engenharia do Porto/ Instituto Politécnico do Porto) - Portugual and ReDCAD at at the university of Sfax - Tunisia.
Estimating the quality of radio links is of paramount importance in WSNs, namely for designing reliable and energy-efficient WSN protocols/mechanisms (e.g. MAC, routing, mobility management, fault-tolerance, deployment, and topology control). For instance, many routing protocols (e.g. CTP(Collection Tree Protocol)) rely on link quality estimation to select higher quality routes. Therefore, it is important to assess the performance of a link quality estimator (LQE) before selecting and integrating it into a particular network protocol/mechanism.
The open-LQE web site includes the following open-source toolset:

RadiaLE software tool: RadiaLE is a benchmarking test-bed that enables the performance evaluation of LQEs. It comprises the hardware components of the WSN test-bed (TelosB nodes, USB cables/hubs) and a software tool for setting up and controlling the experiments and also for analyzing the collected data, allowing for LQEs evaluation (more details are given here). While we built up and validated RadiaLE through a test-bed setup in Porto (Portugal), the idea is that anyone can use it in its own location just by downloading and running the following applications:

TinyOS implementation of several Link Quality Estimators: RadiaLE has a default set of LQEs already implemented (that can be easily extended with any other LQE), but these LQEs can also be used independently from RadiaLE. Therefore, we provide the nesC/TinyOS code for the following LQEs, as follows (tested with TOSSIM 2): Contributors: Nouha Baccour, Maissa Ben Jamaa, Denis do Rosario, Anis Koubaa, Mario Alves, Habib Youssef, and Leandro B. Becker
Web site :


Localization based on Received Signal Strength (RSS) is a key method for locating objects in Wireless Sensor Networks (WSNs). However, current RSS-based methods are ineffective at both deployment and operation design levels. First, they usually require a labor-intensive pre-deployment profiling operations to map the RSS to either locations or distances. Second often rely on heavy processing operations. These two design problems limit the possibility of implementing such localization techniques on resource-constrained sensor nodes, and also restrict their scalability and use in practice. EasyLoc is an autonomous and practical RSS-based localization technique that improves on previous approaches in terms of ease of deployment and ease of implementation, while still providing a reasonable accuracy. EasyLoc is a plug-and-play and fully distributed RSS-based localization method that requires zero pre-deployment configuration.
Contributors: Maissa Ben Jemaa, Anis Koubâa, Nouha Baccour, and Mohamed Jmaiel
Web site: (under-construction)