Internet of Medical Thing (IoMT) is an emerging technology in healthcare that can be used to realize a wide variety of medical applications. It improves people’s quality of life and makes it easier to care for the sick individuals in an efficient and safe manner. To do this, IoMT leverages the capabilities of some new technologies including IoT, Artificial Intelligence, cloud computing, computer networks and medicine. Combining these technologies to monitor the patient’s health conditions in real-time or semi-real-time is a critical challenge in IoMT. In this regard, one of the most crucial components of IoMT are network communication protocols that should provide a fast and reliable communication path between a connected biosensor to a patient and cloud computing environment. In this paper, we propose EQRSRL as an efficient routing mechanism for different types of IoMT applications. The aim of EQRSRL is to provide a reasonable level of Quality of Service (QoS) for IoMT traffics. To achieve this goal, it categorizes the network traffic into three classes and treats them differently concerning their QoS requirements. Moreover, EQRSRL divides the network environment into multiple zones to decrease the number of message exchange between the nodes. In order to compute optimal paths between the nodes, it considers QoS and energy metrics, and makes use of a reinforcement learning approach in path computation process. Simulation results show that the implementation of EQRSRL in IoMT is practical and leads to improvement of 82% in average energy consumption, 25% in end-to-end delay and 7% packet delivery ration in compared to the state-of-the-art routing techniques.

In recent years, the Underwater Internet of Things (IoUT) has become a popular technology for exploring the underwater environment. IoUT enables administrators to explore and monitor underwater environmental phenomena from anywhere in the world where there is Internet access. Due to the harsh underwater environment, the reliability of communication between sensor nodes deteriorates, causing certain performance issues such as higher packet loss rate and long end-to-end delay. Therefore, it is essential to manage the communications between the sensors to address these problems in order to improve the QoS. Software-defined networking (SDN) is one of the most promising architectures for providing efficient network management by decoupling the data plane from the control plane of the network. This paper proposes a new QoS routing technique for SDN-based IoUT aiming at improving QoS by establishing reliable paths between sensor nodes. To do this, the controller gathers the 3D coordinates of each underwater sensor in order to compute the distance between the nodes. Then, it estimates the reliability of each link by using underwater acoustic equations. Finally, it calculates the most reliable path with minimum delay and installs the path on the nodes located along it. The experimental results show that our mechanism significantly outperforms other non-SDN approaches in terms of several performance measures ranging from packet loss ratio and end-to-end delay to energy consumption.