The Internet of Things (IoT) networks comes with many challenges, especially in network architecture designs. IoT is populated by several kinds of devices with different characteristics that are autonomously managed. These devices do not have enough resources and they require to process data in real-time. Hence, there is a need to design suitable architectures for IoT networks that are as efficient as possible. Previously, Cloud Computing (CC) seemed to provide a good solution of processing data from IoT networks. Recently, Mobile Edge Computing (MEC) seems to be offering a better solution than CC by ensuring a better Quality of Services (QoS) provisioning. As a result, many MEC solutions have emerged for QoS improvement in IoT networks. These solutions mainly focus on device resource management without considering data routing from an end-user device to another, especially when the latter are mobile and need to communicate with each other. In this paper, we propose to design an adaptive routing protocol for a MEC-based network to manage efficiently, the end-user devices’ energy consumption during data routing. The proposed adaptive Mobile Edge Computing-based protocol consists of two main phases: firstly, we subdivide the network’s objects into clusters by exploiting a link quality prediction algorithm. Secondly, we route the data to their destination adaptively by considering the object’s movement during the routing process. As presented in the simulation results, our protocol outperforms other existing routing protocols for IoT networks in terms of energy consumption. We then propose the use of our solution for data routing in IoT networks that require huge data processing and forwarding.

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.