Optimizing Coverage in a Wireless Sensors Network by Selecting the Best Sensors

The challenges imposed by wireless sensor networks can be attributed to several factors such as a severe energy constraints, the limited processing and communication capabilities, the dynamic deployment of the environment, the unique data dissemination model, and the quality of service required at the application level. The routing protocol is considered as an important service. It allows to the routing of data packets captured to shift from the sensors to the base station. The choice of the path taken is made according to the performance standards such as energy consumption, reliability, transmission delay, etc. In this work, we will look for the best sensors and the best path to choose in order to set up our sensor network properly. As well, we will optimize the type of sensors for purchasing and the routing of the packets as far as possibility. And consequently, we use a multi-objective function for this purpose. The first part will consist of making the choice between different sensors. As a result, we have the group of sensors which has a minimum communication radius with a cheaper cost, a high throughput, and low-energy consumption. Our results are more optimal in terms of cost, energy, and transfer rate compared to other approaches. The optimization results obtained give us a minimum value for the cost of sensor deployment in the area equal to 218586 FCFA, a minimum value of 1609120 W/h, and a maximum value for the transmission rate equal to 47.82 bit/s. This optimization ensures 91.03% coverage with the square octagon network model.