A Wireless Sensor Network (WSN) is an Ad-hoc network populated by small hand-held commodity devices, running on batteries called stations or sensors. These sensors are deployed in an area called a perception zone in order to study one or more phenomena. Generally, the perception zone is an area where access is almost impossible for humans. Given the absence of a previously defined infrastructure,deployed sensors need to organize themselves to ensure not only their connectivity but also effective management of theirresidual energy. This residual energy management is more important since we know that communications over longdistances are always very energy-consuming for sensors, which most often do not have a secondary source of energy. Multi-hop communication is generally used to connect sensors in order to ensure efficient use of their energy. This being the case, multi-hop communication can be established by partitioning the network into clusters. In order to avoid malicious intrusions, all operations involvedmust be done in a secure manner. In this paper, we propose a secure clustering protocolwhich connects all the sensors of the network.

Wireless sensor networks are increasingly being deployed in areas where several types of information need to be harvested. Monitoring a given area is one of the main goals of this technology. This consists in deploying sensor nodes in the Area of Interest (AoI) in order to detect any event occurring in this area, collect information and send them to the base station. However, in this type of configuration, the quantity and the quality of data collected are important factors in making better decisions by the end user. It therefore becomes crucial to deploy sensors in the AoI so that the latters can cover as much as possible the AoI, and propose mechanism to collect and send data to the base station while minimizing the energy consumption of the sensors. In this paper, we bring into focus a solution (A2CDC) to resolve this problem which performs in two main stages: in the first stage, we propose an algorithm that guarantees a maximal coverage of the AoI after a random deployment of static sensors and mobile sensors; and in the second stage, we propose a node activity scheduling that minimizes energy consumption of both static and mobile nodes while sending collected data to the base station. Compared to many other algorithms in the literature, our solution is better in term of coverage percentage of the AoI, data received by the base station and in term of energy minimization.