The scalability and stability in wireless sensor networks (WSNs) are considering as an important issue due to the large numbers of nodes and consequently their node density and deployment. While the network size increase, the need of scalable and efficient routing protocols is indispensable. Moreover, sensor nodes have to be alive to guarantee the network operation for the period which the first node died doesn’t appear. This period, named network stability region, is ameliorated by many techniques. In fact, the balancing energy consumption and clustering method are among those techniques. In this paper, we present the scalability and stability analysis of the routing protocol LEACH based on K-means clustering algorithm (KLEACH). Accordingly, the simulation results of the performance metrics verify the efficiency and the scalability of KLEACH protocol compared to LEACH.

Many researchers employ ESPRIT method as robust detection tool to identify fault frequency and amplitude in induction machines. However, this algorithm presents some limitation in terms of computational time and required data memory size. This drawback makes this technology unusable in real time diagnosis application. In the fact that wind turbine machine necessitates an on-line regular maintenance to guarantee an acceptable lifetime and to maximize its productivity. Thus, an improved version of ESPRIT-TLS method has been proposed and simulated to extract accurately fault frequencies and their magnitudes from the wind stator current with minimum computation time and less memory cost. The proposed approach has been evaluated by computer simulations under many fault kinds. Study outcomes prove the benefits and the performance of Fast-ESPRIT.

The metrology field has been progressed with the appearance of the wireless intelligent sensor systems providing more capabilities such as signal processing, remote multi-sensing fusion etc. This kind of devices is rapidly making their way into medical and industrial monitoring, collision avoidance, traffic control, automotive and others applications. However, numerous design challenges for wireless intelligent sensors systems are imposed to overcome the physical limitations in data traffic, such as system noise, real time communication, signal attenuation, response dynamics, power consumption, and effective conversion rates etc, especially for applications requiring specific performances. This paper analyzes the performance metrics of the mentioned sensing devices systems which stands for superior measurement, more accuracy and reliability. Study findings prescribe researchers, developers/ engineers and users to realizing an optimal sensing motes design strategy that offers operational advantages which can offer cost-effective solutions for an application.