Cellular networks are constantly evolving to ensure a better Quality of Service (QoS) and quality of coverage ever more important. The radio cellular systems are based on frequency allocation. In this context, frequency allocation principle consists in choosing an optimal frequency plan to meet traffic demand constraints and communication quality while minimizing the radio interferences. This paper proposes an optimal frequency allocation approach based on genetic algorithms to minimize co-channel and adjacent channel interference. The validation of this new approach is confirmed by the results of the work we have done in the GSM network. In fact, we used the file obtained by the OMC-R, which defines the adjacent cells of each cell and the frequencies allocated to the considered area. The results obtained clearly show the effectiveness and robustness of the approach used.

In mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires higher computing power; thus, the most advanced BMS algorithms reported in the literature are developed and verified by laboratory experiments using PC-based software. The objective of this paper is to describe the design of an autonomous and versatile embedded system based on an 8-bit microcontroller, where a Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) algorithm for State of Charge (SOC) estimation is implemented; the developed prototype meets most of the constraints for BMSs reported in the literature, with an energy efficiency of 94% and an error of SOC accuracy that varies between 2% and 8% based on low-cost components.

The new technologies have influenced the world we live in, it is becoming more and more connected; every thing, every object it contains has a virtual image in the digital world. Which also changed the vision of developers towards the Internet of Things, developers spend their time improving their software by adding new features offered by the new connected objects. Therefore the applications must change it behavior in order to be adapted for the new update.Developers spend an important time adapting their applications, reusing or rebuilding new module-based applications, either by composing or by directly reusing modules.These updates depend on the context and nature of this application. Usually, to update an application, we must stop, modify, recompile and restart the application. There may however be cases where this traditional maintenance process can not be applied to certain categories of applications, in which a complete service interruption can not be tolerated. These applications, described as ”non-stop”, must be dynamically reconfigured with minimal disruption.To solve this problem, we propose a system reconfiguration module in real time. Our model is based on a component approach. In this paper, we assume that components are the smallest entities in any system. We summarize the dynamic reconfiguration of a system by automating the disconnection or connection (direct or via an adapter) of components. The new configuration allows the system to achieve its objectives and ensure its proper operation under various conditions imposed by the environment.