Table 1 summarizes the main articles published in the last four years and their goal and QoS strategy. Among different QoS methods, studies focus mainly on four common strategies: (i) scheduling protocols [15,16]; (ii) data prioritization [15,16,17,18,19,20,21,22]; (iii) routing protocols [22,23,24,25,26,27]; (iv) resource management [16,21]. Studies have examined the use of data prioritization to reduce transmission time. This strategy encompasses distinct classes for each data type, prioritizing high-priority packets. Some approaches use admission control algorithms to ensure a network’s quality. Thus, an algorithm checks the current network state and estimates the future state to decide whether to allow new connections. Cloud environments commonly use resource elasticity, and some researchers use it as a way to provide QoS. During overloaded conditions, such strategies use VM allocation and migration strategies to enhance the performance of some modules. Finally, some authors also employ routing and scheduling protocols to improve the performance of networks and reduce transmission delays. The routing algorithms determine the most optimal route for transmitting data based on network conditions. On the other hand, scheduling protocols control the time slot assignment for each data transmission and their order based on the amount and type of data.

Several studies present QoS strategies for Wireless Body Area Network (WBAN) infrastructures [16,22,24,25,26,27,29]. A WBAN comprises a private network of connected sensors transmitting data to a master node that relays the information to upper network layers. Energy consumption and interference are the main problems studies seek to resolve by employing routing protocols and channel selection strategies. Their primary focus is to improve network transmission from the WBAN to the upper network layers. Such strategies can solve the internal problems of WBANs; however, they do not focus on multiple WBANs simultaneously. In other words, initiatives focusing on WBAN propose QoS strategies only within the WBAN boundaries and not the higher level which consumes data. Recent advances employ fog computing as a new solution to bridge the gap between the sensors and the cloud to decrease response time. Some strategies employ fog to provide data processing closer to the sensors and, therefore, remove network hops needed to reach the cloud [30,31]. Despite its advantages, fog solutions still require data extraction and transmission from the sensors and the fog nodes. Depending on the infrastructure, the volume of data and the quality of the transmission channel can still impose restrictions and impact the QoS.

Within a hospital, there are many critical locations, such as operating rooms, in which a system can provide helpful data from patients and physicians. Most strategies focus on remote health sites, like nursing homes, and only WBANs for patient health monitoring. In addition, a healthcare system has two main actors: the sensors at the hardware level, generating information, and the users at the application level, which consume and process data from the system. Strategies focus mainly on the first level to provide QoS in data transmission from the sensor to the network. Furthermore, although some initiatives present concerns regarding real time, they do not focus intensely on this issue. In general, solutions that focus on real time only consider improving time delay from priority packets or providing an architecture that supports real-time data transmissions.